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Force rebag in relevant benchmarks for Voter Bags PR (#9081) #9455

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emostov
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@emostov emostov commented Jul 28, 2021

target PR: #9081
target branch: prgn-nominator-unsorted-bags

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emostov commented Jul 28, 2021

/benchmark runtime pallet_staking

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parity-benchapp bot commented Jul 28, 2021

Error running benchmark: zeke-prgn-nominator-unsorted-bags-rebag-benchmark

stdoutIncomplete command.

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emostov commented Jul 28, 2021

/benchmark runtime pallet pallet_staking

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parity-benchapp bot commented Jul 28, 2021

Benchmark Runtime Pallet for branch "zeke-prgn-nominator-unsorted-bags-rebag-benchmark" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results
2021-07-28 18:40:58 Benchmarking kick 25/64, run 11/20    
2021-07-28 18:41:03 Benchmarking kick 38/64, run 5/20    
2021-07-28 18:41:08 Benchmarking kick 48/64, run 2/20    
2021-07-28 18:41:13 Benchmarking kick 56/64, run 9/20    
2021-07-28 18:41:18 Benchmarking kick 63/64, run 16/20    
2021-07-28 18:41:25 Benchmarking cancel_deferred_slash 27/53, run 4/20    
2021-07-28 18:41:30 Benchmarking cancel_deferred_slash 40/53, run 16/20    
2021-07-28 18:41:35 Benchmarking cancel_deferred_slash 52/53, run 16/20    
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2021-07-28 18:41:40 Benchmarking payout_stakers_dead_controller 8/52, run 1/20    
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2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
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2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:42 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:43 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:44 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 Benchmarking payout_stakers_dead_controller 15/52, run 0/20    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:45 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:46 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:47 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:48 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:49 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:50 Benchmarking payout_stakers_dead_controller 21/52, run 2/20    
2021-07-28 18:41:50 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:51 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:52 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:53 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:54 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:55 Benchmarking payout_stakers_dead_controller 26/52, run 13/20    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:56 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:57 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:58 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:41:59 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:00 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 Benchmarking payout_stakers_dead_controller 31/52, run 15/20    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:01 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:02 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
2021-07-28 18:42:03 [0] 💸 new validator set of size 1 has been processed for era 1    
202<truncated>...

@emostov
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emostov commented Jul 29, 2021

/benchmark runtime pallet pallet_staking

@parity-benchapp
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parity-benchapp bot commented Jul 29, 2021

Benchmark Runtime Pallet for branch "zeke-prgn-nominator-unsorted-bags-rebag-benchmark" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results
Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    75.47
              µs

Reads = 5
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    75.47
              µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    62.26
              µs

Reads = 4
Writes = 2
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    62.26
              µs

Reads = 4
Writes = 2
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    66.87
              µs

Reads = 7
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    66.87
              µs

Reads = 7
Writes = 3
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    52.71
    + s    0.021
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     51.77     0.116    0.2%
    2     52.27     0.098    0.1%
    4     52.51     0.099    0.1%
    6     52.79     0.168    0.3%
    8     52.68     0.061    0.1%
   10     52.41      0.07    0.1%
   12     54.19     0.501    0.9%
   14      53.2       0.1    0.1%
   16     53.39     0.148    0.2%
   18     53.09     0.166    0.3%
   20     53.21     0.125    0.2%
   22     53.23     0.186    0.3%
   24      53.1     0.167    0.3%
   26     53.05     0.115    0.2%
   28     53.53     0.268    0.5%
   30     53.15     0.123    0.2%
   32     53.19     0.158    0.2%
   34     53.94     0.168    0.3%
   36     53.52     0.089    0.1%
   38     53.74     0.178    0.3%
   40     53.62      0.11    0.2%
   42     53.56     0.103    0.1%
   44     53.86     0.147    0.2%
   46     53.92     0.128    0.2%
   48     53.46     0.189    0.3%
   50     54.01     0.111    0.2%
   52     54.27     0.163    0.3%
   54     54.17     0.059    0.1%
   56     54.04     0.097    0.1%
   58     54.05     0.122    0.2%
   60     54.26     0.123    0.2%
   62     54.27     0.112    0.2%
   64     53.82      0.16    0.2%
   66     54.11     0.127    0.2%
   68     54.22     0.086    0.1%
   70     54.38     0.133    0.2%
   72      54.2     0.132    0.2%
   74     54.16      0.13    0.2%
   76     54.37     0.162    0.2%
   78     54.58     0.112    0.2%
   80     54.14     0.141    0.2%
   82     54.26     0.115    0.2%
   84     54.44      0.14    0.2%
   86     54.53      0.08    0.1%
   88     54.22     0.118    0.2%
   90     54.67     0.095    0.1%
   92      54.6     0.157    0.2%
   94     54.78     0.141    0.2%
   96      54.8      0.18    0.3%
   98      54.7     0.094    0.1%
  100      54.5     0.126    0.2%

Quality and confidence:
param     error
s             0

Model:
Time ~=    52.71
    + s    0.021
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    87.79
    + s    2.378
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     82.54     0.212    0.2%
    2      91.2     0.189    0.2%
    4     96.55     0.252    0.2%
    6     101.5     0.187    0.1%
    8       107     0.297    0.2%
   10     110.8     0.139    0.1%
   12     116.3     0.201    0.1%
   14     121.3     0.279    0.2%
   16     125.7      0.12    0.0%
   18     130.5     0.155    0.1%
   20     135.5     0.261    0.1%
   22     140.1     0.318    0.2%
   24     145.6       0.2    0.1%
   26     150.2     0.228    0.1%
   28       155     0.254    0.1%
   30     159.7     0.216    0.1%
   32     164.2      0.41    0.2%
   34       169     0.386    0.2%
   36     173.6     0.333    0.1%
   38     178.1     0.386    0.2%
   40     182.9     0.403    0.2%
   42       188     0.304    0.1%
   44     193.5     0.659    0.3%
   46     198.2     0.501    0.2%
   48       205     1.928    0.9%
   50     205.9     0.515    0.2%
   52     210.8      0.66    0.3%
   54     216.7      0.41    0.1%
   56     221.5     0.535    0.2%
   58     225.7     0.511    0.2%
   60       230     0.466    0.2%
   62     235.1     0.739    0.3%
   64     239.9     0.398    0.1%
   66     244.8     0.406    0.1%
   68     249.3      0.85    0.3%
   70     254.3     0.533    0.2%
   72     258.3     0.891    0.3%
   74     263.1      0.86    0.3%
   76     268.3     0.708    0.2%
   78       273     0.558    0.2%
   80     276.8     0.579    0.2%
   82     281.3     0.336    0.1%
   84     285.7     0.404    0.1%
   86     291.2      0.46    0.1%
   88     295.6     0.459    0.1%
   90     300.3     0.802    0.2%
   92       308      1.09    0.3%
   94     311.3     1.452    0.4%
   96     317.4     1.238    0.3%
   98     322.2     1.344    0.4%
  100     325.5     0.715    0.2%

Quality and confidence:
param     error
s         0.001

Model:
Time ~=    87.52
    + s    2.382
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    71.64
              µs

Reads = 10
Writes = 6
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    71.64
              µs

Reads = 10
Writes = 6
Pallet: "pallet_staking", Extrinsic: "kick", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=       20
    + k    16.95
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    k   mean µs  sigma µs       %
    1     38.23     0.106    0.2%
    3     74.64     0.355    0.4%
    5     106.3     0.137    0.1%
    7     139.9     0.334    0.2%
    9     171.8     0.819    0.4%
   11     205.5     0.569    0.2%
   13     240.3     0.363    0.1%
   15     273.2     0.824    0.3%
   17     307.1     0.999    0.3%
   19       341     0.827    0.2%
   21     377.3     0.998    0.2%
   23     410.9     0.668    0.1%
   25     442.8     1.491    0.3%
   27     480.7     7.822    1.6%
   29     511.9     1.957    0.3%
   31     546.3      0.99    0.1%
   33     580.4     1.543    0.2%
   35     612.1     2.941    0.4%
   37       648     1.648    0.2%
   39     676.3     1.682    0.2%
   41     715.9     5.869    0.8%
   43       745     2.007    0.2%
   45     775.5     1.952    0.2%
   47     813.2     3.648    0.4%
   49     843.9     2.674    0.3%
   51       886     6.854    0.7%
   53     920.6     5.611    0.6%
   55     953.9     9.583    1.0%
   57     983.4     7.928    0.8%
   59      1016     8.611    0.8%
   61      1052     12.32    1.1%
   63      1087     9.967    0.9%
   65      1122     2.961    0.2%
   67      1160     12.77    1.1%
   69      1186     2.795    0.2%
   71      1224     8.604    0.7%
   73      1251     3.924    0.3%
   75      1287      10.5    0.8%
   77      1311     3.702    0.2%
   79      1355     5.447    0.4%
   81      1384      14.7    1.0%
   83      1426     9.374    0.6%
   85      1473     17.25    1.1%
   87      1491     10.13    0.6%
   89      1518     8.092    0.5%
   91      1550     8.774    0.5%
   93      1590     9.088    0.5%
   95      1630     4.981    0.3%
   97      1655     9.794    0.5%
   99      1705     10.95    0.6%
  101      1720     13.98    0.8%
  103      1774     9.679    0.5%
  105      1798     10.19    0.5%
  107      1841     14.73    0.7%
  109      1870     4.109    0.2%
  111      1920     8.028    0.4%
  113      1966     13.78    0.7%
  115      1976     9.313    0.4%
  117      2014     8.981    0.4%
  119      2052     10.96    0.5%
  121      2089     16.84    0.8%
  123      2116     5.386    0.2%
  125      2155     9.403    0.4%
  127      2198     14.44    0.6%

Quality and confidence:
param     error
k         0.011

Model:
Time ~=    15.76
    + k    17.03
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    90.37
    + n    5.735
              µs

Reads = 12 + (1 * n)
Writes = 7 + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     94.23     0.375    0.3%
    2     101.9     0.275    0.2%
    3     107.5     0.244    0.2%
    4     113.3     0.384    0.3%
    5     120.3     0.308    0.2%
    6     127.4     0.217    0.1%
    7     130.7     0.127    0.0%
    8     135.6     0.255    0.1%
    9     140.6     0.489    0.3%
   10     147.7     0.441    0.2%
   11     153.2     0.501    0.3%
   12     158.3     0.606    0.3%
   13     165.3     0.529    0.3%
   14     171.2     0.569    0.3%
   15     175.5     0.664    0.3%
   16     182.2     0.658    0.3%

Quality and confidence:
param     error
n         0.019

Model:
Time ~=    90.39
    + n    5.731
              µs

Reads = 12 + (1 * n)
Writes = 7 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    18.68
              µs

Reads = 3
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    18.68
              µs

Reads = 3
Writes = 0
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    12.95
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    12.95
              µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    27.52
              µs

Reads = 3
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    27.52
              µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.623
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.623
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.816
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.816
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.793
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.793
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.821
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.821
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    3.083
    + v    0.055
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
    0     2.778     0.011    0.3%
   20     4.218     0.024    0.5%
   40     5.435     0.025    0.4%
   60     6.528     0.018    0.2%
   80     7.624      0.04    0.5%
  100      8.67     0.029    0.3%
  120     9.943     0.025    0.2%
  140     10.92     0.031    0.2%
  160     12.06     0.026    0.2%
  180     13.12     0.023    0.1%
  200     14.26     0.031    0.2%
  220     15.38     0.028    0.1%
  240     16.51     0.028    0.1%
  260     17.61     0.048    0.2%
  280     18.78     0.028    0.1%
  300     19.84     0.021    0.1%
  320     20.83     0.034    0.1%
  340     21.95     0.018    0.0%
  360     23.13     0.042    0.1%
  380     24.32     0.024    0.0%
  400     25.46     0.028    0.1%
  420     26.58     0.026    0.0%
  440     27.57     0.015    0.0%
  460     28.83     0.045    0.1%
  480     29.75     0.018    0.0%
  500     30.77     0.042    0.1%
  520     32.18     0.067    0.2%
  540     33.33     0.043    0.1%
  560     34.37     0.021    0.0%
  580     35.43     0.027    0.0%
  600     36.61     0.037    0.1%
  620     37.87     0.029    0.0%
  640     38.81     0.045    0.1%
  660     39.96     0.032    0.0%
  680      41.1     0.046    0.1%
  700     42.28     0.024    0.0%
  720     43.36     0.038    0.0%
  740     44.44     0.033    0.0%
  760     45.47     0.064    0.1%
  780     46.63     0.063    0.1%
  800     47.69     0.046    0.0%
  820     48.95     0.047    0.0%
  840     50.09     0.035    0.0%
  860     51.26     0.028    0.0%
  880     52.35     0.041    0.0%
  900     53.46     0.045    0.0%
  920     54.57     0.011    0.0%
  940     55.67     0.036    0.0%
  960      56.8     0.046    0.0%
  980      57.9     0.011    0.0%
 1000     59.01     0.044    0.0%

Quality and confidence:
param     error
v             0

Model:
Time ~=    3.062
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    63.22
    + s     2.45
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     59.05     0.218    0.3%
    2     67.23      0.13    0.1%
    4     72.31     0.132    0.1%
    6     77.86     0.243    0.3%
    8     82.56     0.168    0.2%
   10     87.79     0.063    0.0%
   12     92.49      0.21    0.2%
   14     97.64     0.198    0.2%
   16     102.9     0.246    0.2%
   18     107.5     0.196    0.1%
   20     112.1     0.166    0.1%
   22     117.6     0.391    0.3%
   24     122.5     0.137    0.1%
   26     127.1     0.317    0.2%
   28       132     0.211    0.1%
   30     137.2     0.203    0.1%
   32     142.1      0.28    0.1%
   34     146.4     0.341    0.2%
   36     151.7     0.349    0.2%
   38     156.8     0.185    0.1%
   40     161.4     0.339    0.2%
   42     166.5     0.177    0.1%
   44     170.7     0.383    0.2%
   46     176.6     0.418    0.2%
   48     180.7     0.386    0.2%
   50     185.2     0.408    0.2%
   52     190.3     0.365    0.1%
   54     195.9     0.855    0.4%
   56     200.5     0.353    0.1%
   58       205     0.506    0.2%
   60     209.4     0.375    0.1%
   62     215.7     0.568    0.2%
   64     219.1     0.377    0.1%
   66     224.6     0.245    0.1%
   68     229.8     0.309    0.1%
   70     234.4     0.355    0.1%
   72     238.6     0.544    0.2%
   74     245.2     0.877    0.3%
   76     248.7     0.479    0.1%
   78       254     1.994    0.7%
   80     259.3     0.504    0.1%
   82     264.9     1.525    0.5%
   84     267.2     0.429    0.1%
   86     273.2     0.477    0.1%
   88     278.9     1.088    0.3%
   90     283.2     0.882    0.3%
   92     289.7     0.981    0.3%
   94     294.1     1.101    0.3%
   96     298.6     0.481    0.1%
   98     303.3     0.869    0.2%
  100     308.3     0.868    0.2%

Quality and confidence:
param     error
s         0.001

Model:
Time ~=    62.95
    + s    2.454
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     3827
    + s    19.96
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1     257.8     0.196    0.0%
   20      1000     9.249    0.9%
   39      1746      10.9    0.6%
   58      2450     17.69    0.7%
   77      3148     16.15    0.5%
   96      3837     11.46    0.2%
  115      4541     20.61    0.4%
  134      5249     0.864    0.0%
  153      5822     10.61    0.1%
  172      6460     20.58    0.3%
  191      7041     13.35    0.1%
  210      7695     26.47    0.3%
  229      8240     9.565    0.1%
  248      8812     16.36    0.1%
  267      9370     18.87    0.2%
  286      9924     27.46    0.2%
  305     10450     34.61    0.3%
  324     10930     12.08    0.1%
  343     11450     29.23    0.2%
  362     11950     16.58    0.1%
  381     12420     19.84    0.1%
  400     12860     18.39    0.1%
  419     13330     26.82    0.2%
  438     13740     12.67    0.0%
  457     14160     26.17    0.1%
  476     14550     11.19    0.0%
  495     14930     11.92    0.0%
  514     15320     19.61    0.1%
  533     15670     28.79    0.1%
  552     16030     31.55    0.1%
  571     16410     44.33    0.2%
  590     16640     28.22    0.1%
  609     16950     12.39    0.0%
  628     17260     28.85    0.1%
  647     17490     17.43    0.0%
  666     17800     28.06    0.1%
  685     18000     15.53    0.0%
  704     18270      27.5    0.1%
  723     18450     22.76    0.1%
  742     18650     21.11    0.1%
  761     18840     21.77    0.1%
  780     19020     44.84    0.2%
  799     19190     36.51    0.1%
  818     19340     30.08    0.1%
  837     19450     33.31    0.1%
  856     19560     23.67    0.1%
  875     19660     16.99    0.0%
  894     19750     38.57    0.1%
  913     19820     28.38    0.1%
  932     19880     46.93    0.2%
  951     19920     24.41    0.1%
  970     19960     42.68    0.2%
  989     20140     148.8    0.7%

Quality and confidence:
param     error
s         0.222

Model:
Time ~=     3405
    + s    19.95
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    112.1
    + n    49.37
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     162.4     0.378    0.2%
    6     410.4     1.391    0.3%
   11     655.3      0.82    0.1%
   16     903.6     3.192    0.3%
   21      1144     2.147    0.1%
   26      1399     8.792    0.6%
   31      1642     12.62    0.7%
   36      1897     12.47    0.6%
   41      2137     10.45    0.4%
   46      2387     12.59    0.5%
   51      2626     19.95    0.7%
   56      2885     8.853    0.3%
   61      3106      21.2    0.6%
   66      3333     12.91    0.3%
   71      3618     7.263    0.2%
   76      3849     7.664    0.1%
   81      4105     18.15    0.4%
   86      4368     14.27    0.3%
   91      4592     10.45    0.2%
   96      4824     7.636    0.1%
  101      5043     7.422    0.1%
  106      5349     13.32    0.2%
  111      5558     16.19    0.2%
  116      5809     13.65    0.2%
  121      6064      15.1    0.2%
  126      6311     18.36    0.2%
  131      6553     18.06    0.2%
  136      6803     14.62    0.2%
  141      7035     14.27    0.2%
  146      7340     13.25    0.1%
  151      7586     30.28    0.3%
  156      7847     31.51    0.4%
  161      8154     21.55    0.2%
  166      8338      17.4    0.2%
  171      8611      33.4    0.3%
  176      8850     19.62    0.2%
  181      9067     20.24    0.2%
  186      9333     23.49    0.2%
  191      9545     17.85    0.1%
  196      9830     27.03    0.2%
  201     10030     16.13    0.1%
  206     10270     28.19    0.2%
  211     10500     26.22    0.2%
  216     10800     28.82    0.2%
  221     11050     34.82    0.3%
  226     11320     27.66    0.2%
  231     11480     15.29    0.1%
  236     11720     19.53    0.1%
  241     12020     18.22    0.1%
  246     12210     21.68    0.1%
  251     12480     18.19    0.1%
  256     12720      27.1    0.2%

Quality and confidence:
param     error
n          0.02

Model:
Time ~=    106.7
    + n    49.41
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    152.9
    + n    63.33
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     205.5     0.615    0.2%
    6     525.7     1.522    0.2%
   11       842     1.891    0.2%
   16      1184     16.49    1.3%
   21      1489     7.404    0.4%
   26      1805     11.86    0.6%
   31      2111     20.74    0.9%
   36      2452     10.95    0.4%
   41      2727     9.847    0.3%
   46      3059     10.94    0.3%
   51      3400     9.208    0.2%
   56      3700        14    0.3%
   61      4011     13.55    0.3%
   66      4299     8.065    0.1%
   71      4638     11.52    0.2%
   76      4935     20.49    0.4%
   81      5264     7.734    0.1%
   86      5593     14.94    0.2%
   91      5932     10.66    0.1%
   96      6256     19.82    0.3%
  101      6560     17.06    0.2%
  106      6886     20.88    0.3%
  111      7199     6.706    0.0%
  116      7496     16.49    0.2%
  121      7797     17.88    0.2%
  126      8176     21.04    0.2%
  131      8480     16.11    0.1%
  136      8795     25.34    0.2%
  141      9107     16.97    0.1%
  146      9339     21.53    0.2%
  151      9721     21.82    0.2%
  156      9949     25.91    0.2%
  161     10240     26.61    0.2%
  166     10630     25.02    0.2%
  171     10990     50.77    0.4%
  176     11340     32.77    0.2%
  181     11660      25.4    0.2%
  186     11960     10.86    0.0%
  191     12290     17.05    0.1%
  196     12600     30.37    0.2%
  201     12870     28.14    0.2%
  206     13170     19.49    0.1%
  211     13500     23.54    0.1%
  216     13810     23.91    0.1%
  221     14310     185.7    1.2%
  226     14460     48.82    0.3%
  231     14740     53.63    0.3%
  236     15150     34.92    0.2%
  241     15320     43.53    0.2%
  246     15690     37.09    0.2%
  251     16070      39.2    0.2%
  256     16340     51.17    0.3%

Quality and confidence:
param     error
n         0.031

Model:
Time ~=      151
    + n    63.35
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    55.25
    + l    0.068
              µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    l   mean µs  sigma µs       %
    1      55.5     0.111    0.1%
    2     55.33     0.102    0.1%
    3     54.92     0.111    0.2%
    4     55.13     0.065    0.1%
    5     55.87     0.174    0.3%
    6     55.63     0.207    0.3%
    7     55.56     0.113    0.2%
    8     55.77     0.123    0.2%
    9     55.93     0.111    0.1%
   10     56.06     0.166    0.2%
   11     55.98     0.203    0.3%
   12     56.46     0.158    0.2%
   13     56.17      0.13    0.2%
   14     56.06     0.077    0.1%
   15     56.27     0.109    0.1%
   16     56.31     0.146    0.2%
   17     56.91     0.153    0.2%
   18     56.74     0.098    0.1%
   19     56.72     0.159    0.2%
   20      56.7     0.117    0.2%
   21     56.89     0.142    0.2%
   22     56.85     0.175    0.3%
   23     56.93     0.137    0.2%
   24     56.57     0.211    0.3%
   25     57.43     0.199    0.3%
   26     57.79     0.523    0.9%
   27     56.98     0.159    0.2%
   28     56.82     0.154    0.2%
   29     57.53     0.196    0.3%
   30     56.71     0.231    0.4%
   31     57.08     0.135    0.2%
   32     57.22     0.184    0.3%

Quality and confidence:
param     error
l         0.002

Model:
Time ~=    55.26
    + l    0.069
              µs

Reads = 4 + (0 * l)
Writes = 3 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + e    35.46
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    e   mean µs  sigma µs       %
    1     43.48     0.073    0.1%
    2     71.53      0.09    0.1%
    3     97.81     0.181    0.1%
    4     127.1      0.25    0.1%
    5     153.1      0.24    0.1%
    6     179.5     0.297    0.1%
    7     205.1     0.216    0.1%
    8     233.6     0.488    0.2%
    9       260     0.467    0.1%
   10     290.5     0.577    0.1%
   11     318.1     0.436    0.1%
   12     346.8     0.336    0.0%
   13     372.6     0.927    0.2%
   14       404     0.588    0.1%
   15     433.6     1.783    0.4%
   16     463.3     0.859    0.1%
   17     495.2     0.729    0.1%
   18     522.7     1.414    0.2%
   19     552.4     1.171    0.2%
   20     582.7     1.033    0.1%
   21     615.5     4.588    0.7%
   22     644.5     0.803    0.1%
   23       676     2.278    0.3%
   24     711.2     4.812    0.6%
   25     745.3     1.276    0.1%
   26     774.9     2.785    0.3%
   27     813.3     1.988    0.2%
   28     841.2     7.904    0.9%
   29       867     2.595    0.2%
   30     906.8      0.96    0.1%
   31     946.1     6.371    0.6%
   32     969.1     1.997    0.2%
   33      1002     10.75    1.0%
   34      1034      2.71    0.2%
   35      1073     7.215    0.6%
   36      1101     4.717    0.4%
   37      1128     11.11    0.9%
   38      1154      3.95    0.3%
   39      1191     2.918    0.2%
   40      1228     6.181    0.5%
   41      1262     3.501    0.2%
   42      1285     6.698    0.5%
   43      1323     3.743    0.2%
   44      1371     8.638    0.6%
   45      1407     16.17    1.1%
   46      1427     3.916    0.2%
   47      1476      14.5    0.9%
   48      1517     8.907    0.5%
   49      1558     11.49    0.7%
   50      1560     7.317    0.4%
   51      1628     8.956    0.5%
   52      1670     8.164    0.4%
   53      1710     10.33    0.6%
   54      1704     6.394    0.3%
   55      1775      15.9    0.8%
   56      1816     9.378    0.5%
   57      1849     11.29    0.6%
   58      1866      7.45    0.3%
   59      1921     14.42    0.7%
   60      1938     9.934    0.5%
   61      1983     11.79    0.5%
   62      2027     14.46    0.7%
   63      2061     9.035    0.4%
   64      2088     13.78    0.6%
   65      2144     10.87    0.5%
   66      2172     17.53    0.8%
   67      2209      12.3    0.5%
   68      2247     14.04    0.6%
   69      2258     11.51    0.5%
   70      2315     15.92    0.6%
   71      2349     15.71    0.6%
   72      2379     14.84    0.6%
   73      2434     14.67    0.6%
   74      2489     13.32    0.5%
   75      2521     12.74    0.5%
   76      2563     9.327    0.3%
   77      2642     16.15    0.6%
   78      2681     4.283    0.1%
   79      2689     13.42    0.4%
   80      2716     10.23    0.3%
   81      2751     6.583    0.2%
   82      2796     7.722    0.2%
   83      2826     13.59    0.4%
   84      2892     11.37    0.3%
   85      2947      7.46    0.2%
   86      2949     10.82    0.3%
   87      2986     6.928    0.2%
   88      3070     6.037    0.1%
   89      3086     9.369    0.3%
   90      3175     4.303    0.1%
   91      3158     14.32    0.4%
   92      3238     9.283    0.2%
   93      3264     14.27    0.4%
   94      3299     22.19    0.6%
   95      3329     12.96    0.3%
   96      3415     10.08    0.2%
   97      3434     12.03    0.3%
   98      3448     7.267    0.2%
   99      3545     14.69    0.4%
  100      3587     11.97    0.3%

Quality and confidence:
param     error
e          0.07

Model:
Time ~=        0
    + e    35.67
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    103.6
    + s    2.369
              µs

Reads = 11 + (0 * s)
Writes = 12 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1       105     0.166    0.1%
    2       107     0.092    0.0%
    3     109.7     0.291    0.2%
    4     111.4     0.149    0.1%
    5     114.8     0.077    0.0%
    6     116.7     0.218    0.1%
    7     119.5     0.186    0.1%
    8     121.8     0.275    0.2%
    9     124.6     0.284    0.2%
   10     126.8     0.371    0.2%
   11     129.1     0.281    0.2%
   12     131.8     0.244    0.1%
   13     133.6      0.27    0.2%
   14     136.2     0.379    0.2%
   15       139     0.232    0.1%
   16     140.9     0.224    0.1%
   17     144.1     0.177    0.1%
   18     145.7     0.329    0.2%
   19     149.2     0.561    0.3%
   20     151.6     0.266    0.1%
   21     153.3     0.207    0.1%
   22     155.8     0.216    0.1%
   23     158.2     0.225    0.1%
   24     161.3     0.173    0.1%
   25     163.5     0.312    0.1%
   26     165.7     0.235    0.1%
   27     168.3     0.458    0.2%
   28     170.8     0.269    0.1%
   29       173     0.323    0.1%
   30     175.1     0.274    0.1%
   31     177.4     0.222    0.1%
   32     180.3     0.396    0.2%
   33     182.1     0.251    0.1%
   34     184.7     0.203    0.1%
   35     187.8     0.325    0.1%
   36     189.4     0.265    0.1%
   37     192.2     0.293    0.1%
   38       194     0.112    0.0%
   39     196.2     0.347    0.1%
   40     199.3      0.32    0.1%
   41     201.1     0.549    0.2%
   42       204     0.536    0.2%
   43     205.8     0.284    0.1%
   44     208.2     0.289    0.1%
   45     210.9      0.24    0.1%
   46     213.2     0.252    0.1%
   47     215.7      0.42    0.1%
   48     218.5     0.511    0.2%
   49       221     0.534    0.2%
   50     222.2      0.52    0.2%
   51     224.6     0.374    0.1%
   52     226.7     0.181    0.0%
   53     229.3     0.865    0.3%
   54     231.3     0.263    0.1%
   55     234.6     0.505    0.2%
   56     236.9     0.617    0.2%
   57       239       0.8    0.3%
   58     241.2     0.569    0.2%
   59     243.5     0.321    0.1%
   60     245.3     0.575    0.2%
   61     254.4     11.02    4.3%
   62     250.8     0.799    0.3%
   63     253.4     0.519    0.2%
   64     255.8     0.685    0.2%
   65     257.1     0.483    0.1%
   66     259.6     0.724    0.2%
   67     261.5     0.524    0.2%
   68     265.5     1.317    0.4%
   69     266.7      0.83    0.3%
   70     268.7      0.87    0.3%
   71     271.6     0.534    0.1%
   72     274.3     0.745    0.2%
   73     276.4     0.517    0.1%
   74     278.4     0.496    0.1%
   75     280.4     0.579    0.2%
   76     283.2     0.726    0.2%
   77     285.7     0.753    0.2%
   78     287.5     0.798    0.2%
   79     290.2     0.695    0.2%
   80     292.8     0.843    0.2%
   81     292.7     0.459    0.1%
   82     296.9      0.46    0.1%
   83     303.7     4.896    1.6%
   84     300.8     0.711    0.2%
   85     303.7     0.846    0.2%
   86     306.5     0.525    0.1%
   87     309.8     0.749    0.2%
   88     311.3     0.982    0.3%
   89     314.7     0.562    0.1%
   90     315.5     0.915    0.2%
   91     318.9     0.709    0.2%
   92     321.4     0.732    0.2%
   93     324.9     1.364    0.4%
   94     327.5     1.097    0.3%
   95     328.1     0.802    0.2%
   96     329.3     0.735    0.2%
   97     332.7     0.819    0.2%
   98     336.3     1.261    0.3%
   99       339     1.127    0.3%
  100     341.4      1.05    0.3%

Quality and confidence:
param     error
s         0.001

Model:
Time ~=    103.6
    + s     2.37
              µs

Reads = 11 + (0 * s)
Writes = 12 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    292.3
    + n    51.57
              µs

Reads = 209 + (4 * v) + (4 * n)
Writes = 4 + (3 * v) + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
    1   100      3899     12.71    0.3%
    2   100      4217      10.7    0.2%
    3   100      4441     16.17    0.3%
    4   100      4594     13.16    0.2%
    5   100      4929     14.23    0.2%
    6   100      5217     18.85    0.3%
    7   100      5485     32.42    0.5%
    8   100      5778      14.7    0.2%
    9   100      6224     14.29    0.2%
   10     1      1409     12.95    0.9%
   10     2      1482      15.2    1.0%
   10     3      1540     15.78    1.0%
   10     4      1586     6.965    0.4%
   10     5      1652     14.11    0.8%
   10     6      1697     14.24    0.8%
   10     7      1741     14.45    0.8%
   10     8      1804     8.553    0.4%
   10     9      1843     9.049    0.4%
   10    10      1908     12.25    0.6%
   10    11      1963     21.44    1.0%
   10    12      2002     14.33    0.7%
   10    13      2060     12.77    0.6%
   10    14      2135     15.95    0.7%
   10    15      2193      6.73    0.3%
   10    16      2209     17.36    0.7%
   10    17      2271     15.31    0.6%
   10    18      2338     14.78    0.6%
   10    19      2375     13.17    0.5%
   10    20      2433     9.209    0.3%
   10    21      2450     7.975    0.3%
   10    22      2496     6.912    0.2%
   10    23      2563     11.57    0.4%
   10    24      2631     13.12    0.4%
   10    25      2679     19.19    0.7%
   10    26      2753     12.96    0.4%
   10    27      2792     12.77    0.4%
   10    28      2862      10.7    0.3%
   10    29      2901     9.952    0.3%
   10    30      2956     15.91    0.5%
   10    31      3003     15.04    0.5%
   10    32      3064     11.91    0.3%
   10    33      3131     14.75    0.4%
   10    34      3162     9.954    0.3%
   10    35      3232     16.12    0.4%
   10    36      3293     21.73    0.6%
   10    37      3334     14.32    0.4%
   10    38      3385     8.869    0.2%
   10    39      3421     14.77    0.4%
   10    40      3465     16.06    0.4%
   10    41      3534     18.95    0.5%
   10    42      3543     10.18    0.2%
   10    43      3639      13.6    0.3%
   10    44      3645     14.28    0.3%
   10    45      3727     11.66    0.3%
   10    46      3760     14.35    0.3%
   10    47      3802      11.2    0.2%
   10    48      3864     16.67    0.4%
   10    49      3864     8.811    0.2%
   10    50      3986     15.21    0.3%
   10    51      4011     10.33    0.2%
   10    52      4058      16.3    0.4%
   10    53      4155     12.16    0.2%
   10    54      4148     18.58    0.4%
   10    55      4256     13.84    0.3%
   10    56      4297     11.51    0.2%
   10    57      4329     6.849    0.1%
   10    58      4398     11.08    0.2%
   10    59      4458     6.294    0.1%
   10    60      4498      12.7    0.2%
   10    61      4543     16.84    0.3%
   10    62      4600     14.65    0.3%
   10    63      4661     6.569    0.1%
   10    64      4734     13.91    0.2%
   10    65      4783      10.9    0.2%
   10    66      4787      14.5    0.3%
   10    67      4893     13.84    0.2%
   10    68      4911     7.422    0.1%
   10    69      4919     8.639    0.1%
   10    70      5123     25.13    0.4%
   10    71      5050     14.57    0.2%
   10    72      5145     15.58    0.3%
   10    73      5196     10.35    0.1%
   10    74      5200     12.96    0.2%
   10    75      5278     12.63    0.2%
   10    76      5336     11.08    0.2%
   10    77      5335     13.11    0.2%
   10    78      5384     21.26    0.3%
   10    79      5420     15.49    0.2%
   10    80      5557     17.57    0.3%
   10    81      5538     9.937    0.1%
   10    82      5612     11.39    0.2%
   10    83      5685     9.496    0.1%
   10    84      5722     11.35    0.1%
   10    85      5799     13.84    0.2%
   10    86      5780     21.35    0.3%
   10    87      5894     32.46    0.5%
   10    88      5898     8.505    0.1%
   10    89      5957     13.31    0.2%
   10    90      6087     11.02    0.1%
   10    91      6049     24.66    0.4%
   10    92      6177     19.18    0.3%
   10    93      6095     10.97    0.1%
   10    94      6234     10.57    0.1%
   10    95      6286     17.86    0.2%
   10    96      6361     13.72    0.2%
   10    97      6397     14.96    0.2%
   10    98      6426     18.47    0.2%
   10    99      6510     16.82    0.2%
   10   100      6532     17.17    0.2%

Quality and confidence:
param     error
v         0.901
n         0.045

Model:
Time ~=        0
    + v    305.4
    + n    51.35
              µs

Reads = 209 + (4 * v) + (4 * n)
Writes = 4 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    25.24
    + n    34.35
    + s    54.99
              µs

Reads = 201 + (3 * v) + (4 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n     s   mean µs  sigma µs       %
  500  1000    20     44040       183    0.4%
  510  1000    20     44350     134.5    0.3%
  520  1000    20     44650     194.4    0.4%
  530  1000    20     44750     216.2    0.4%
  540  1000    20     44700     195.3    0.4%
  550  1000    20     45150     303.1    0.6%
  560  1000    20     46040     113.8    0.2%
  570  1000    20     45180     179.2    0.3%
  580  1000    20     45730     124.9    0.2%
  590  1000    20     46000     162.5    0.3%
  600  1000    20     45940     127.9    0.2%
  610  1000    20     46810     138.7    0.2%
  620  1000    20     46750     305.5    0.6%
  630  1000    20     47150     147.1    0.3%
  640  1000    20     47150     208.7    0.4%
  650  1000    20     47740     214.1    0.4%
  660  1000    20     47850     62.04    0.1%
  670  1000    20     47870     184.2    0.3%
  680  1000    20     48220     199.7    0.4%
  690  1000    20     48440     171.7    0.3%
  700  1000    20     49030     156.5    0.3%
  710  1000    20     49430       250    0.5%
  720  1000    20     49260     89.21    0.1%
  730  1000    20     49690     168.3    0.3%
  740  1000    20     49940     163.5    0.3%
  750  1000    20     49750     161.8    0.3%
  760  1000    20     50720     112.5    0.2%
  770  1000    20     50470     108.1    0.2%
  780  1000    20     50540     156.6    0.3%
  790  1000    20     51210     212.1    0.4%
  800  1000    20     51020     230.2    0.4%
  810  1000    20     51420     136.7    0.2%
  820  1000    20     51200     187.6    0.3%
  830  1000    20     52650     196.2    0.3%
  840  1000    20     52040     194.9    0.3%
  850  1000    20     52170     175.5    0.3%
  860  1000    20     51850       187    0.3%
  870  1000    20     52750     249.3    0.4%
  880  1000    20     52970     206.1    0.3%
  890  1000    20     53040     205.3    0.3%
  900  1000    20     54250     136.7    0.2%
  910  1000    20     54350     134.4    0.2%
  920  1000    20     54470     271.7    0.4%
  930  1000    20     54160       205    0.3%
  940  1000    20     54730     187.2    0.3%
  950  1000    20     54320     130.9    0.2%
  960  1000    20     55660     207.7    0.3%
  970  1000    20     55860       152    0.2%
  980  1000    20     55830     320.1    0.5%
  990  1000    20     57270     328.9    0.5%
 1000   500    20     39100     185.4    0.4%
 1000   510    20     40160     176.9    0.4%
 1000   520    20     40220     118.7    0.2%
 1000   530    20     40360     170.7    0.4%
 1000   540    20     41000     83.66    0.2%
 1000   550    20     41010     95.61    0.2%
 1000   560    20     40910     113.6    0.2%
 1000   570    20     40980     163.1    0.3%
 1000   580    20     41730       155    0.3%
 1000   590    20     42270     82.89    0.1%
 1000   600    20     42440     118.3    0.2%
 1000   610    20     42800     144.3    0.3%
 1000   620    20     43390     191.8    0.4%
 1000   630    20     43980     123.7    0.2%
 1000   640    20     44130     123.4    0.2%
 1000   650    20     44280     165.4    0.3%
 1000   660    20     44770     189.4    0.4%
 1000   670    20     45090     157.2    0.3%
 1000   680    20     45990     117.1    0.2%
 1000   690    20     46030     166.3    0.3%
 1000   700    20     46010     148.6    0.3%
 1000   710    20     46020       186    0.4%
 1000   720    20     46270     190.4    0.4%
 1000   730    20     47470     100.5    0.2%
 1000   740    20     47120     251.5    0.5%
 1000   750    20     47320     238.5    0.5%
 1000   760    20     48470       187    0.3%
 1000   770    20     48920     239.3    0.4%
 1000   780    20     48870     160.6    0.3%
 1000   790    20     48520     201.4    0.4%
 1000   800    20     49020     229.5    0.4%
 1000   810    20     49790     189.7    0.3%
 1000   820    20     49690     408.4    0.8%
 1000   830    20     50700     160.2    0.3%
 1000   840    20     50510     289.6    0.5%
 1000   850    20     50920     87.27    0.1%
 1000   860    20     51220     342.7    0.6%
 1000   870    20     51910     128.6    0.2%
 1000   880    20     51510     180.8    0.3%
 1000   890    20     52410     113.8    0.2%
 1000   900    20     53000     298.9    0.5%
 1000   910    20     53570     175.2    0.3%
 1000   920    20     52830     159.3    0.3%
 1000   930    20     53110     192.5    0.3%
 1000   940    20     54330       266    0.4%
 1000   950    20     54600     129.3    0.2%
 1000   960    20     54260     290.9    0.5%
 1000   970    20     55370     283.4    0.5%
 1000   980    20     55740     313.1    0.5%
 1000   990    20     56750     212.7    0.3%
 1000  1000     1     56540       373    0.6%
 1000  1000     2     56510     193.1    0.3%
 1000  1000     3     55590     104.3    0.1%
 1000  1000     4     56890     197.3    0.3%
 1000  1000     5     56580     182.9    0.3%
 1000  1000     6     56350     118.2    0.2%
 1000  1000     7     57060     205.1    0.3%
 1000  1000     8     56700     280.4    0.4%
 1000  1000     9     56960     135.5    0.2%
 1000  1000    10     55930       105    0.1%
 1000  1000    11     57060     169.9    0.2%
 1000  1000    12     56060     201.1    0.3%
 1000  1000    13     57120     159.4    0.2%
 1000  1000    14     56240     191.5    0.3%
 1000  1000    15     57180     256.2    0.4%
 1000  1000    16     56590     252.3    0.4%
 1000  1000    17     57130     241.1    0.4%
 1000  1000    18     57070     133.9    0.2%
 1000  1000    19     57240     231.9    0.4%
 1000  1000    20     57550     181.2    0.3%

Quality and confidence:
param     error
v         0.109
n         0.109
s         3.736

Model:
Time ~=        0
    + v    25.31
    + n     34.6
    + s        0
              µs

Reads = 201 + (3 * v) + (4 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Pallet: "pallet_staking", Extrinsic: "get_npos_targets", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    11.68
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
  500      5832     20.95    0.3%
  510      5721     42.17    0.7%
  520      5901     38.55    0.6%
  530      5997     19.38    0.3%
  540      6321     31.58    0.4%
  550      6394     36.61    0.5%
  560      6301     42.19    0.6%
  570      6543     20.39    0.3%
  580      6572     36.66    0.5%
  590      6887      58.6    0.8%
  600      6927     29.21    0.4%
  610      7043     43.84    0.6%
  620      7221        38    0.5%
  630      7124     19.25    0.2%
  640      7488     42.32    0.5%
  650      7428     34.99    0.4%
  660      7532     38.15    0.5%
  670      7868     35.75    0.4%
  680      7960     36.99    0.4%
  690      7863     40.02    0.5%
  700      8079     40.44    0.5%
  710      8076     29.47    0.3%
  720      8406      56.6    0.6%
  730      8388     42.27    0.5%
  740      8478     39.21    0.4%
  750      8649     39.77    0.4%
  760      8628     41.23    0.4%
  770      8880     34.76    0.3%
  780      8914     26.47    0.2%
  790      8872     55.69    0.6%
  800      9208     42.21    0.4%
  810      9456     42.43    0.4%
  820      9381     24.69    0.2%
  830      9636     62.43    0.6%
  840      9657     48.69    0.5%
  850      9741     37.13    0.3%
  860      9807     44.16    0.4%
  870      9950     30.63    0.3%
  880     10310     67.05    0.6%
  890     10150      63.9    0.6%
  900     10360     56.87    0.5%
  910     10490     77.82    0.7%
  920     10890     56.12    0.5%
  930     10870     47.76    0.4%
  940     10840     46.84    0.4%
  950     10930     54.32    0.4%
  960     11090     66.57    0.6%
  970     11310     72.12    0.6%
  980     11220     80.74    0.7%
  990     11460      87.6    0.7%
 1000     11720     55.17    0.4%

Quality and confidence:
param     error
v         0.033

Model:
Time ~=        0
    + v     11.7
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "set_staking_limits", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6.65
              µs

Reads = 0
Writes = 5
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6.65
              µs

Reads = 0
Writes = 5
Pallet: "pallet_staking", Extrinsic: "chill_other", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     92.1
              µs

Reads = 11
Writes = 6
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     92.1
              µs

Reads = 11
Writes = 6
Pallet: "pallet_staking", Extrinsic: "rebag", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    88.11
              µs

Reads = 7
Writes = 5
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    88.11
              µs

Reads = 7
Writes = 5
Pallet: "pallet_staking", Extrinsic: "regenerate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    42.84
    + n     44.2
              µs

Reads = 2 + (3 * v) + (3 * n)
Writes = 2 + (2 * v) + (2 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
  500  1000     61740     83.64    0.1%
  510  1000     62440     205.7    0.3%
  520  1000     62240     133.4    0.2%
  530  1000     62200     234.6    0.3%
  540  1000     63470     193.6    0.3%
  550  1000     63530     102.6    0.1%
  560  1000     64240     232.1    0.3%
  570  1000     64430     116.5    0.1%
  580  1000     65550     124.2    0.1%
  590  1000     64570     152.6    0.2%
  600  1000     65970     132.8    0.2%
  610  1000     66790     169.8    0.2%
  620  1000     66480     180.8    0.2%
  630  1000     67310       248    0.3%
  640  1000     67800     133.3    0.1%
  650  1000     68350     130.4    0.1%
  660  1000     69030     172.9    0.2%
  670  1000     69630     237.1    0.3%
  680  1000     68970     172.7    0.2%
  690  1000     69400     214.1    0.3%
  700  1000     69580     233.9    0.3%
  710  1000     70910     139.2    0.1%
  720  1000     70370     217.5    0.3%
  730  1000     71170     164.2    0.2%
  740  1000     71240     313.2    0.4%
  750  1000     72830     151.3    0.2%
  760  1000     72610     95.44    0.1%
  770  1000     73110     299.1    0.4%
  780  1000     72850     267.4    0.3%
  790  1000     74360     183.8    0.2%
  800  1000     75070     181.8    0.2%
  810  1000     75110     177.1    0.2%
  820  1000     75240     213.8    0.2%
  830  1000     76240       199    0.2%
  840  1000     76290     242.8    0.3%
  850  1000     76210     158.6    0.2%
  860  1000     77650     153.9    0.1%
  870  1000     77570     174.6    0.2%
  880  1000     78060     163.6    0.2%
  890  1000     78110     96.94    0.1%
  900  1000     78540     282.9    0.3%
  910  1000     79060     468.9    0.5%
  920  1000     80090     232.9    0.2%
  930  1000     79500     183.3    0.2%
  940  1000     80120     134.9    0.1%
  950  1000     81090     283.6    0.3%
  960  1000     81800     100.3    0.1%
  970  1000     80520     120.7    0.1%
  980  1000     82020     244.7    0.2%
  990  1000     82240     311.9    0.3%
 1000   500     60760     160.9    0.2%
 1000   510     61010     163.5    0.2%
 1000   520     62280     159.2    0.2%
 1000   530     62570     254.3    0.4%
 1000   540     62050     282.1    0.4%
 1000   550     62990     177.7    0.2%
 1000   560     63620      99.1    0.1%
 1000   570     63720     117.5    0.1%
 1000   580     64110       191    0.2%
 1000   590     65030     84.56    0.1%
 1000   600     64980     134.1    0.2%
 1000   610     65830     96.64    0.1%
 1000   620     65670     117.7    0.1%
 1000   630     66670     167.3    0.2%
 1000   640     66970     114.6    0.1%
 1000   650     67570     174.3    0.2%
 1000   660     67320     167.5    0.2%
 1000   670     67620     165.6    0.2%
 1000   680     68730     207.8    0.3%
 1000   690     68330       241    0.3%
 1000   700     69660     174.3    0.2%
 1000   710     69800     115.9    0.1%
 1000   720     70520     146.2    0.2%
 1000   730     70260     166.4    0.2%
 1000   740     71920       240    0.3%
 1000   750     71940     232.7    0.3%
 1000   760     72420     292.8    0.4%
 1000   770     73070     171.9    0.2%
 1000   780     72400     104.5    0.1%
 1000   790     72940     322.8    0.4%
 1000   800     73930     171.8    0.2%
 1000   810     74340     187.5    0.2%
 1000   820     74840     236.7    0.3%
 1000   830     75170     230.5    0.3%
 1000   840     75250     134.2    0.1%
 1000   850     75600     143.8    0.1%
 1000   860     76470     165.2    0.2%
 1000   870     76660     175.4    0.2%
 1000   880     77410     86.68    0.1%
 1000   890     78160     159.7    0.2%
 1000   900     78700     256.1    0.3%
 1000   910     78260     121.3    0.1%
 1000   920     79660     138.8    0.1%
 1000   930     79780     270.6    0.3%
 1000   940     80300     258.2    0.3%
 1000   950     80770     195.6    0.2%
 1000   960     80220     216.8    0.2%
 1000   970     81840     133.8    0.1%
 1000   980     81920     232.8    0.2%
 1000   990     82490     198.9    0.2%
 1000  1000     83480     248.6    0.2%

Quality and confidence:
param     error
v         0.109
n         0.109

Model:
Time ~=        0
    + v    42.38
    + n    44.43
              µs

Reads = 2 + (3 * v) + (3 * n)
Writes = 2 + (2 * v) + (2 * n)

Parity Benchmarking Bot and others added 8 commits July 29, 2021 04:00
…path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic=* --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs
string: &'static str,
n: u32,
balance_factor: crate::BalanceOf<T>,
) -> T::AccountId {
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I made this just so we could take BalanceOf<T> for balance_factor instead of u32, because in theory the threshold we select could overflow a u32. But it seems strange because now create_funded_user just wraps this function (look above). We could replace create_funded_user with this and just call .into on all the existing balance_factor arguments, but that would make this diff a bit more annoying (although we could do a small pr to update master with this). @kianenigma thoughts?

@emostov emostov marked this pull request as ready for review July 30, 2021 05:34
@emostov emostov requested a review from kianenigma as a code owner July 30, 2021 05:34
@emostov emostov requested a review from athei as a code owner July 30, 2021 05:36
@emostov emostov removed the request for review from athei July 30, 2021 05:40
@paritytech paritytech deleted a comment from parity-benchapp bot Jul 30, 2021
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emostov commented Jul 30, 2021

/benchmark runtime pallet pallet_staking

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parity-benchapp bot commented Jul 30, 2021

Benchmark Runtime Pallet for branch "zeke-prgn-nominator-unsorted-bags-rebag-benchmark" with command cargo run --quiet --release --features=runtime-benchmarks --manifest-path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic="*" --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs

Results
Pallet: "pallet_staking", Extrinsic: "bond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    75.61
              µs

Reads = 5
Writes = 4
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    75.61
              µs

Reads = 5
Writes = 4
Pallet: "pallet_staking", Extrinsic: "bond_extra", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    147.5
              µs

Reads = 10
Writes = 9
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    147.5
              µs

Reads = 10
Writes = 9
Pallet: "pallet_staking", Extrinsic: "unbond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=      156
              µs

Reads = 15
Writes = 10
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=      156
              µs

Reads = 15
Writes = 10
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_update", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     53.4
    + s    0.022
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     52.19     0.074    0.1%
    2     52.97     0.066    0.1%
    4     53.15     0.083    0.1%
    6     53.14     0.105    0.1%
    8     53.28     0.163    0.3%
   10     52.96     0.206    0.3%
   12     53.94     0.226    0.4%
   14     53.67     0.132    0.2%
   16     53.79     0.137    0.2%
   18      53.7     0.074    0.1%
   20     53.99     0.131    0.2%
   22     54.12     0.116    0.2%
   24     53.92     0.115    0.2%
   26     53.97     0.112    0.2%
   28     54.37     0.206    0.3%
   30     54.32      0.17    0.3%
   32     54.33     0.183    0.3%
   34      54.1     0.092    0.1%
   36     54.79     0.533    0.9%
   38     54.48     0.127    0.2%
   40     54.55     0.097    0.1%
   42     54.62     0.101    0.1%
   44     54.61     0.104    0.1%
   46     54.64     0.113    0.2%
   48      54.6     0.106    0.1%
   50     54.88      0.16    0.2%
   52     54.85     0.168    0.3%
   54     54.66     0.155    0.2%
   56     54.74     0.113    0.2%
   58     54.86     0.202    0.3%
   60     54.71     0.096    0.1%
   62     54.74     0.119    0.2%
   64     55.07     0.152    0.2%
   66     54.95     0.068    0.1%
   68      55.1     0.141    0.2%
   70     54.83     0.116    0.2%
   72     55.26     0.095    0.1%
   74     55.17     0.112    0.2%
   76     55.35     0.105    0.1%
   78     55.29     0.148    0.2%
   80     55.33     0.076    0.1%
   82        55     0.125    0.2%
   84     55.01       0.1    0.1%
   86        55     0.154    0.2%
   88     55.14     0.072    0.1%
   90     55.22     0.152    0.2%
   92     55.29      0.14    0.2%
   94     55.42     0.207    0.3%
   96     55.19     0.134    0.2%
   98     55.35     0.089    0.1%
  100     55.35     0.084    0.1%

Quality and confidence:
param     error
s             0

Model:
Time ~=    53.35
    + s    0.023
              µs

Reads = 4 + (0 * s)
Writes = 3 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "withdraw_unbonded_kill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    89.03
    + s    2.398
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0      83.3     0.155    0.1%
    2     91.77     0.234    0.2%
    4     97.71     0.301    0.3%
    6     102.4     0.188    0.1%
    8     107.2     0.122    0.1%
   10     112.7     0.207    0.1%
   12     118.3      0.25    0.2%
   14     123.1     0.263    0.2%
   16     127.7     0.144    0.1%
   18     132.5     0.318    0.2%
   20       137     0.255    0.1%
   22     142.4     0.125    0.0%
   24     147.3     0.132    0.0%
   26     152.1     0.468    0.3%
   28     156.6     0.348    0.2%
   30     161.4     0.318    0.1%
   32     165.8     0.294    0.1%
   34     170.6     0.241    0.1%
   36     175.4     0.119    0.0%
   38     180.2     0.306    0.1%
   40     185.1     0.489    0.2%
   42       191      0.82    0.4%
   44     194.8     0.456    0.2%
   46     199.7     0.754    0.3%
   48     204.8     0.379    0.1%
   50     208.7     0.573    0.2%
   52     214.2     0.766    0.3%
   54     218.4     0.378    0.1%
   56     224.1     0.481    0.2%
   58     228.4     0.381    0.1%
   60     233.4      0.48    0.2%
   62     238.6     0.562    0.2%
   64     242.5     0.581    0.2%
   66     247.3     0.648    0.2%
   68       252     0.397    0.1%
   70     256.4     0.465    0.1%
   72     261.1     0.477    0.1%
   74     267.1      0.78    0.2%
   76     270.3     0.635    0.2%
   78     275.6     0.541    0.1%
   80     279.9     0.753    0.2%
   82     288.2     5.333    1.8%
   84     289.8     1.172    0.4%
   86     293.1      0.51    0.1%
   88     299.1     1.144    0.3%
   90     302.9     0.698    0.2%
   92     310.1     0.633    0.2%
   94     314.1     0.595    0.1%
   96     319.2     0.274    0.0%
   98     324.2     1.074    0.3%
  100     329.7     0.893    0.2%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    88.67
    + s    2.404
              µs

Reads = 8 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "validate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     72.5
              µs

Reads = 10
Writes = 6
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     72.5
              µs

Reads = 10
Writes = 6
Pallet: "pallet_staking", Extrinsic: "kick", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    21.18
    + k    16.89
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    k   mean µs  sigma µs       %
    1     38.47     0.143    0.3%
    3     74.25     0.277    0.3%
    5     106.6     0.394    0.3%
    7     140.7     0.218    0.1%
    9     172.3      0.32    0.1%
   11     206.5     0.361    0.1%
   13     241.2     0.631    0.2%
   15     273.7     0.862    0.3%
   17     309.9     1.231    0.3%
   19     340.5     0.531    0.1%
   21       380     1.645    0.4%
   23     410.4         1    0.2%
   25     451.9     10.04    2.2%
   27     484.4     11.82    2.4%
   29     509.7     1.272    0.2%
   31     542.3      0.95    0.1%
   33     578.1     1.377    0.2%
   35     610.1     1.708    0.2%
   37     653.5     12.91    1.9%
   39     680.6     2.061    0.3%
   41     714.2     1.405    0.1%
   43     743.3      1.17    0.1%
   45     775.6     1.411    0.1%
   47     818.5     11.21    1.3%
   49     846.1     2.036    0.2%
   51     880.6     3.266    0.3%
   53     914.4     5.314    0.5%
   55     948.6     3.599    0.3%
   57       979     3.914    0.3%
   59      1016     9.695    0.9%
   61      1043     2.641    0.2%
   63      1090     9.255    0.8%
   65      1118     3.218    0.2%
   67      1152      6.54    0.5%
   69      1199     15.53    1.2%
   71      1217     3.037    0.2%
   73      1252     10.44    0.8%
   75      1286     9.764    0.7%
   77      1320     6.069    0.4%
   79      1349     4.145    0.3%
   81      1386     9.069    0.6%
   83      1420     5.425    0.3%
   85      1453     8.347    0.5%
   87      1490     10.08    0.6%
   89      1538     18.19    1.1%
   91      1572     12.93    0.8%
   93      1580      9.03    0.5%
   95      1628     11.21    0.6%
   97      1651     13.05    0.7%
   99      1688      10.8    0.6%
  101      1716      7.84    0.4%
  103      1765     8.331    0.4%
  105      1805      12.9    0.7%
  107      1827      10.2    0.5%
  109      1883     16.88    0.8%
  111      1914     13.21    0.6%
  113      1970     12.25    0.6%
  115      2004      20.1    1.0%
  117      2004     11.43    0.5%
  119      2049      8.25    0.4%
  121      2078     12.59    0.6%
  123      2112     11.07    0.5%
  125      2160     11.65    0.5%
  127      2181     12.57    0.5%

Quality and confidence:
param     error
k         0.013

Model:
Time ~=    16.74
    + k    17.01
              µs

Reads = 1 + (1 * k)
Writes = 0 + (1 * k)
Pallet: "pallet_staking", Extrinsic: "nominate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    90.43
    + n    5.694
              µs

Reads = 12 + (1 * n)
Writes = 7 + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     94.24     0.317    0.3%
    2     102.8     0.512    0.4%
    3     106.2     0.251    0.2%
    4     113.3     0.317    0.2%
    5     120.4     0.248    0.2%
    6     126.4     0.465    0.3%
    7     130.9     0.334    0.2%
    8       135     0.327    0.2%
    9     140.7     0.249    0.1%
   10     147.8     0.364    0.2%
   11     152.2     0.437    0.2%
   12       158     0.556    0.3%
   13     164.8     0.893    0.5%
   14     169.5     0.289    0.1%
   15       175     0.509    0.2%
   16     182.6     0.289    0.1%

Quality and confidence:
param     error
n         0.019

Model:
Time ~=    90.34
    + n    5.699
              µs

Reads = 12 + (1 * n)
Writes = 7 + (0 * n)
Pallet: "pallet_staking", Extrinsic: "chill", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    18.85
              µs

Reads = 3
Writes = 0
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    18.85
              µs

Reads = 3
Writes = 0
Pallet: "pallet_staking", Extrinsic: "set_payee", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.27
              µs

Reads = 1
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    13.27
              µs

Reads = 1
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    27.98
              µs

Reads = 3
Writes = 3
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    27.98
              µs

Reads = 3
Writes = 3
Pallet: "pallet_staking", Extrinsic: "set_validator_count", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     2.52
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     2.52
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_no_eras", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.787
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.787
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.726
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.726
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "force_new_era_always", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.819
              µs

Reads = 0
Writes = 1
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    2.819
              µs

Reads = 0
Writes = 1
Pallet: "pallet_staking", Extrinsic: "set_invulnerables", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    3.019
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
    0     2.765     0.018    0.6%
   20     4.197      0.02    0.4%
   40     5.382     0.021    0.3%
   60     6.529     0.028    0.4%
   80     7.591     0.047    0.6%
  100     8.642     0.018    0.2%
  120     9.793     0.037    0.3%
  140     10.87     0.024    0.2%
  160     12.01     0.036    0.2%
  180     13.18     0.046    0.3%
  200     14.31     0.027    0.1%
  220     15.31     0.035    0.2%
  240     16.53     0.024    0.1%
  260     17.59     0.028    0.1%
  280      18.7     0.037    0.1%
  300     19.87      0.03    0.1%
  320     20.91     0.026    0.1%
  340     22.06     0.032    0.1%
  360     23.23     0.034    0.1%
  380     24.28     0.017    0.0%
  400     25.38     0.038    0.1%
  420     26.56     0.018    0.0%
  440     27.73     0.035    0.1%
  460     28.83     0.037    0.1%
  480     29.93     0.041    0.1%
  500     30.88     0.022    0.0%
  520      32.3     0.076    0.2%
  540      33.3     0.031    0.0%
  560     34.51     0.037    0.1%
  580     35.65      0.05    0.1%
  600     36.74     0.027    0.0%
  620     37.95     0.037    0.0%
  640     38.96     0.057    0.1%
  660     40.02     0.031    0.0%
  680     41.09     0.044    0.1%
  700      42.4      0.03    0.0%
  720     43.45     0.045    0.1%
  740     44.59     0.038    0.0%
  760      45.7     0.044    0.0%
  780     46.81     0.054    0.1%
  800     48.04      0.05    0.1%
  820     49.12      0.05    0.1%
  840     50.22     0.064    0.1%
  860      51.4     0.018    0.0%
  880     52.46      0.03    0.0%
  900     53.57     0.034    0.0%
  920     54.74     0.031    0.0%
  940      55.9     0.058    0.1%
  960     56.87     0.049    0.0%
  980     58.04     0.049    0.0%
 1000     59.22     0.043    0.0%

Quality and confidence:
param     error
v             0

Model:
Time ~=    3.009
    + v    0.056
              µs

Reads = 0 + (0 * v)
Writes = 1 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "force_unstake", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    63.96
    + s    2.453
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    0     59.33     0.092    0.1%
    2     67.91     0.101    0.1%
    4     72.55     0.218    0.3%
    6     78.43     0.097    0.1%
    8     83.32     0.123    0.1%
   10      88.1     0.112    0.1%
   12     93.21     0.099    0.1%
   14     98.99     0.261    0.2%
   16     103.9     0.131    0.1%
   18     108.7     0.197    0.1%
   20     113.5     0.343    0.3%
   22     118.6     0.192    0.1%
   24     123.2     0.213    0.1%
   26     128.1     0.254    0.1%
   28     132.9     0.375    0.2%
   30       139     1.483    1.0%
   32     143.2     1.377    0.9%
   34     147.2     0.222    0.1%
   36     152.7     0.199    0.1%
   38       157     0.346    0.2%
   40     161.9     0.233    0.1%
   42     167.1     0.429    0.2%
   44       172     0.239    0.1%
   46     178.1     0.293    0.1%
   48     181.6     0.319    0.1%
   50     186.3      0.36    0.1%
   52     191.6     0.526    0.2%
   54     196.4     0.618    0.3%
   56     201.3      0.32    0.1%
   58     206.9     0.246    0.1%
   60     210.6     0.582    0.2%
   62     216.5     0.424    0.1%
   64     220.6     0.106    0.0%
   66     224.9     0.353    0.1%
   68     230.4     0.385    0.1%
   70     235.8     0.511    0.2%
   72     240.5     0.486    0.2%
   74     246.1     0.466    0.1%
   76       250     0.385    0.1%
   78     255.4     1.326    0.5%
   80     259.9     0.471    0.1%
   82     263.7     0.718    0.2%
   84     269.3     0.863    0.3%
   86     273.2     0.757    0.2%
   88     279.2     0.853    0.3%
   90     284.3     1.509    0.5%
   92       290     0.627    0.2%
   94     294.4     0.727    0.2%
   96     299.5      0.83    0.2%
   98     304.4     0.559    0.1%
  100     313.2     5.973    1.9%

Quality and confidence:
param     error
s         0.002

Model:
Time ~=    63.69
    + s    2.458
              µs

Reads = 6 + (0 * s)
Writes = 6 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "cancel_deferred_slash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     3830
    + s    19.94
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1     246.8     0.303    0.1%
   20     991.5     8.957    0.9%
   39      1718     11.75    0.6%
   58      2434     13.69    0.5%
   77      3134     12.88    0.4%
   96      3819      9.83    0.2%
  115      4491     3.425    0.0%
  134      5152     10.45    0.2%
  153      5802     13.09    0.2%
  172      6440     21.06    0.3%
  191      7035        13    0.1%
  210      7652     15.59    0.2%
  229      8237     19.59    0.2%
  248      8794     7.909    0.0%
  267      9368     14.92    0.1%
  286      9896     15.56    0.1%
  305     10420     23.42    0.2%
  324     10930     13.74    0.1%
  343     11450     20.96    0.1%
  362     11940     17.72    0.1%
  381     12390     22.99    0.1%
  400     12850     17.98    0.1%
  419     13310     28.49    0.2%
  438     13720     31.95    0.2%
  457     14130     28.47    0.2%
  476     14530     35.14    0.2%
  495     14920     25.39    0.1%
  514     15300     21.95    0.1%
  533     15650     20.77    0.1%
  552     16000     21.85    0.1%
  571     16350     24.22    0.1%
  590     16630     17.39    0.1%
  609     16970     26.82    0.1%
  628     17210     36.24    0.2%
  647     17510     26.83    0.1%
  666     17750     26.21    0.1%
  685     18000     29.88    0.1%
  704     18230     16.94    0.0%
  723     18440     26.32    0.1%
  742     18650     27.35    0.1%
  761     18840     27.46    0.1%
  780     19000     21.99    0.1%
  799     19170     26.65    0.1%
  818     19310     24.85    0.1%
  837     19440     35.37    0.1%
  856     19560     21.29    0.1%
  875     19660     31.11    0.1%
  894     19760     25.57    0.1%
  913     19800      25.8    0.1%
  932     19890     34.94    0.1%
  951     19900     26.96    0.1%
  970     19950     35.67    0.1%
  989     19970     20.76    0.1%

Quality and confidence:
param     error
s         0.223

Model:
Time ~=     3384
    + s    19.95
              µs

Reads = 1 + (0 * s)
Writes = 1 + (0 * s)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_dead_controller", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    121.6
    + n    48.64
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     169.1     1.025    0.6%
    6     418.7     6.566    1.5%
   11     655.6     1.919    0.2%
   16     903.6     2.825    0.3%
   21      1140     2.006    0.1%
   26      1379      2.26    0.1%
   31      1626     11.75    0.7%
   36      1885     13.87    0.7%
   41      2108      4.83    0.2%
   46      2353     15.64    0.6%
   51      2575     11.24    0.4%
   56      2851     13.11    0.4%
   61      3087     17.05    0.5%
   66      3328     11.33    0.3%
   71      3581     14.88    0.4%
   76      3825     8.792    0.2%
   81      4069     7.714    0.1%
   86      4281     13.51    0.3%
   91      4523     13.45    0.2%
   96      4807     15.88    0.3%
  101      5013     25.01    0.4%
  106      5257     16.29    0.3%
  111      5482     11.14    0.2%
  116      5747     15.53    0.2%
  121      6001     17.79    0.2%
  126      6265     9.631    0.1%
  131      6496     14.01    0.2%
  136      6732     12.49    0.1%
  141      6970     18.44    0.2%
  146      7217     15.57    0.2%
  151      7468     20.68    0.2%
  156      7761     13.64    0.1%
  161      8022       8.8    0.1%
  166      8272     20.11    0.2%
  171      8436     15.24    0.1%
  176      8727     31.47    0.3%
  181      9006     19.76    0.2%
  186      9236     15.23    0.1%
  191      9423     23.46    0.2%
  196      9687     14.73    0.1%
  201      9965     29.65    0.2%
  206     10180     28.47    0.2%
  211     10440      28.5    0.2%
  216     10610     24.56    0.2%
  221     10860     19.66    0.1%
  226     11060     18.34    0.1%
  231     11290     16.73    0.1%
  236     11600     19.48    0.1%
  241     11800      22.4    0.1%
  246     12040     28.79    0.2%
  251     12310     13.12    0.1%
  256     12530     29.91    0.2%

Quality and confidence:
param     error
n         0.021

Model:
Time ~=    122.1
    + n    48.66
              µs

Reads = 10 + (3 * n)
Writes = 2 + (1 * n)
Pallet: "pallet_staking", Extrinsic: "payout_stakers_alive_staked", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    159.7
    + n       63
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    n   mean µs  sigma µs       %
    1     212.3     0.541    0.2%
    6     531.7     1.743    0.3%
   11     850.2     1.755    0.2%
   16      1172     8.411    0.7%
   21      1492     12.52    0.8%
   26      1798     3.033    0.1%
   31      2104     11.51    0.5%
   36      2409     11.23    0.4%
   41      2743     14.55    0.5%
   46      3078     13.68    0.4%
   51      3381     9.589    0.2%
   56      3673     8.606    0.2%
   61      3984     8.521    0.2%
   66      4288     6.385    0.1%
   71      4627     17.83    0.3%
   76      4927      12.5    0.2%
   81      5264     27.13    0.5%
   86      5557      10.5    0.1%
   91      5905     16.09    0.2%
   96      6238     14.68    0.2%
  101      6537     14.55    0.2%
  106      6851     13.39    0.1%
  111      7194     13.26    0.1%
  116      7513     15.71    0.2%
  121      7809     9.562    0.1%
  126      8108     22.75    0.2%
  131      8426     42.52    0.5%
  136      8737     20.91    0.2%
  141      9088      28.3    0.3%
  146      9362     26.99    0.2%
  151      9680     26.31    0.2%
  156      9944      17.9    0.1%
  161     10270     24.56    0.2%
  166     10580     19.12    0.1%
  171     10870     28.55    0.2%
  176     11220     24.28    0.2%
  181     11640     22.06    0.1%
  186     11870     29.39    0.2%
  191     12250     39.51    0.3%
  196     12560     36.66    0.2%
  201     12810     41.98    0.3%
  206     13190     31.68    0.2%
  211     13540     49.87    0.3%
  216     13700     34.64    0.2%
  221     14060     30.08    0.2%
  226     14350     17.34    0.1%
  231     14690     23.34    0.1%
  236     15030     13.65    0.0%
  241     15330      36.6    0.2%
  246     15690     28.98    0.1%
  251     16010     48.92    0.3%
  256     16190     23.82    0.1%

Quality and confidence:
param     error
n         0.024

Model:
Time ~=    160.6
    + n    63.02
              µs

Reads = 11 + (5 * n)
Writes = 3 + (3 * n)
Pallet: "pallet_staking", Extrinsic: "rebond", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=      140
    + l    0.082
              µs

Reads = 11 + (0 * l)
Writes = 10 + (0 * l)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    l   mean µs  sigma µs       %
    1     140.4     0.436    0.3%
    2     139.9     0.277    0.1%
    3     140.1     0.364    0.2%
    4     139.7     0.276    0.1%
    5     140.9     0.263    0.1%
    6     139.9      0.17    0.1%
    7     140.7     0.233    0.1%
    8     140.7     0.164    0.1%
    9     140.4     0.296    0.2%
   10     140.5     0.078    0.0%
   11     141.2     0.145    0.1%
   12       141      0.17    0.1%
   13     141.2     0.255    0.1%
   14     141.4     0.465    0.3%
   15     141.7     0.298    0.2%
   16     140.9     0.268    0.1%
   17     140.9     0.286    0.2%
   18     141.7     0.301    0.2%
   19     141.5     0.279    0.1%
   20     142.1      1.39    0.9%
   21     141.1     0.215    0.1%
   22     142.1     0.221    0.1%
   23       142     0.217    0.1%
   24     141.9     0.206    0.1%
   25     142.3     0.121    0.0%
   26     142.3     0.213    0.1%
   27     141.7     0.301    0.2%
   28     142.4     0.237    0.1%
   29     141.9     0.229    0.1%
   30     142.4       0.2    0.1%
   31     142.4     0.214    0.1%
   32       143     0.304    0.2%

Quality and confidence:
param     error
l         0.002

Model:
Time ~=    139.9
    + l    0.083
              µs

Reads = 11 + (0 * l)
Writes = 10 + (0 * l)
Pallet: "pallet_staking", Extrinsic: "set_history_depth", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + e    35.02
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    e   mean µs  sigma µs       %
    1     42.56     0.127    0.2%
    2     69.78     0.132    0.1%
    3     95.48     0.166    0.1%
    4     124.8      0.14    0.1%
    5     149.5     0.203    0.1%
    6     175.5     0.441    0.2%
    7     203.1     0.399    0.1%
    8     228.3     0.346    0.1%
    9     258.2     1.251    0.4%
   10     286.6     0.776    0.2%
   11     313.4     0.482    0.1%
   12     340.3     0.456    0.1%
   13     369.2     0.752    0.2%
   14     397.6     0.895    0.2%
   15     425.1     0.542    0.1%
   16     453.6     0.815    0.1%
   17     484.6     0.802    0.1%
   18     512.9     1.473    0.2%
   19     546.9      1.18    0.2%
   20     571.4     0.632    0.1%
   21     604.8     2.102    0.3%
   22     638.2     3.006    0.4%
   23     663.7     0.785    0.1%
   24     697.7     0.752    0.1%
   25     730.1     1.967    0.2%
   26     761.6      2.41    0.3%
   27     801.8      9.05    1.1%
   28     827.5     1.478    0.1%
   29     861.6     6.205    0.7%
   30       896     6.404    0.7%
   31     929.3     8.672    0.9%
   32     954.2      1.74    0.1%
   33     991.4     3.264    0.3%
   34      1023     1.468    0.1%
   35      1057     1.869    0.1%
   36      1104     14.14    1.2%
   37      1112     17.66    1.5%
   38      1143     7.814    0.6%
   39      1170     8.572    0.7%
   40      1197     2.558    0.2%
   41      1237     6.828    0.5%
   42      1273     11.09    0.8%
   43      1311       9.4    0.7%
   44      1349     8.026    0.5%
   45      1381     11.76    0.8%
   46      1412     9.695    0.6%
   47      1443     3.603    0.2%
   48      1490     7.127    0.4%
   49      1533     9.183    0.5%
   50      1546     9.555    0.6%
   51      1602     7.269    0.4%
   52      1644     11.16    0.6%
   53      1673     10.04    0.6%
   54      1720     13.65    0.7%
   55      1735     8.175    0.4%
   56      1787     7.225    0.4%
   57      1823     15.29    0.8%
   58      1844     13.94    0.7%
   59      1894     14.25    0.7%
   60      1941     16.71    0.8%
   61      1966     10.11    0.5%
   62      1996     14.29    0.7%
   63      2023     11.12    0.5%
   64      2061      19.6    0.9%
   65      2105     15.95    0.7%
   66      2140     10.65    0.4%
   67      2169     24.88    1.1%
   68      2204      11.4    0.5%
   69      2246     14.34    0.6%
   70      2278     8.803    0.3%
   71      2335     20.57    0.8%
   72      2355      13.5    0.5%
   73      2398     14.92    0.6%
   74      2448     11.25    0.4%
   75      2473      8.62    0.3%
   76      2499     10.21    0.4%
   77      2574     11.08    0.4%
   78      2596     10.06    0.3%
   79      2633     12.39    0.4%
   80      2680     15.15    0.5%
   81      2718     12.19    0.4%
   82      2776     15.22    0.5%
   83      2832     19.26    0.6%
   84      2865     11.24    0.3%
   85      2915     10.43    0.3%
   86      2955     17.12    0.5%
   87      2948     12.31    0.4%
   88      3066      20.4    0.6%
   89      3050      10.6    0.3%
   90      3126     17.05    0.5%
   91      3171      9.03    0.2%
   92      3200     13.36    0.4%
   93      3221     10.99    0.3%
   94      3256     12.78    0.3%
   95      3310     17.45    0.5%
   96      3352     18.37    0.5%
   97      3390     12.23    0.3%
   98      3428     10.62    0.3%
   99      3503     7.645    0.2%
  100      3538     14.74    0.4%

Quality and confidence:
param     error
e         0.072

Model:
Time ~=        0
    + e    35.28
              µs

Reads = 2 + (0 * e)
Writes = 4 + (7 * e)
Pallet: "pallet_staking", Extrinsic: "reap_stash", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    104.4
    + s    2.399
              µs

Reads = 11 + (0 * s)
Writes = 12 + (1 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    s   mean µs  sigma µs       %
    1     105.5     0.162    0.1%
    2     108.3     0.223    0.2%
    3     110.6      0.23    0.2%
    4     112.8     0.212    0.1%
    5     115.5     0.261    0.2%
    6     117.9     0.202    0.1%
    7     120.3      0.16    0.1%
    8       123     0.179    0.1%
    9     126.3     0.201    0.1%
   10       128     0.139    0.1%
   11     130.6     0.119    0.0%
   12     133.4     0.101    0.0%
   13     135.5     0.335    0.2%
   14     137.5     0.191    0.1%
   15     141.1     0.203    0.1%
   16     142.9     0.334    0.2%
   17     145.6     0.322    0.2%
   18     147.4     0.179    0.1%
   19     150.4      0.21    0.1%
   20       153     0.241    0.1%
   21     154.4     0.452    0.2%
   22     157.6     0.264    0.1%
   23     159.9     0.388    0.2%
   24     162.6     0.234    0.1%
   25     164.8     0.266    0.1%
   26     167.3     0.264    0.1%
   27       170     0.288    0.1%
   28     172.4     0.533    0.3%
   29     174.7     0.425    0.2%
   30     177.6     0.414    0.2%
   31     178.9     0.255    0.1%
   32       182      0.31    0.1%
   33       184     0.284    0.1%
   34     185.6     0.191    0.1%
   35     189.2     0.373    0.1%
   36     191.1     0.162    0.0%
   37     193.3     0.298    0.1%
   38     195.2     0.313    0.1%
   39     197.6     0.358    0.1%
   40     201.3     0.465    0.2%
   41     203.6     0.661    0.3%
   42     205.5     0.324    0.1%
   43     207.3     0.346    0.1%
   44     210.7     0.488    0.2%
   45     212.2     0.249    0.1%
   46     215.2     0.309    0.1%
   47     218.1     0.491    0.2%
   48     220.1     0.631    0.2%
   49     222.7     0.588    0.2%
   50     224.4     0.454    0.2%
   51     226.8     0.722    0.3%
   52     228.6     0.447    0.1%
   53     231.2     0.514    0.2%
   54     234.1     0.207    0.0%
   55     236.9     0.326    0.1%
   56     238.3     0.243    0.1%
   57     241.4     0.374    0.1%
   58       245     2.183    0.8%
   59     246.5     0.486    0.1%
   60       248     0.571    0.2%
   61     251.5     0.547    0.2%
   62     253.3      0.64    0.2%
   63     255.7     0.489    0.1%
   64     258.7     0.721    0.2%
   65     260.4     0.348    0.1%
   66     262.3     0.438    0.1%
   67     264.4     0.252    0.0%
   68     267.2     0.572    0.2%
   69     271.2     1.085    0.4%
   70     271.2     0.433    0.1%
   71       275     0.961    0.3%
   72       277     0.321    0.1%
   73     280.1      0.94    0.3%
   74     281.8     0.641    0.2%
   75     283.4     0.683    0.2%
   76     286.9     0.973    0.3%
   77     290.2     0.814    0.2%
   78     292.1      1.13    0.3%
   79     293.6     0.631    0.2%
   80     295.2     0.543    0.1%
   81       297     1.197    0.4%
   82     299.9     0.595    0.1%
   83     303.4     1.277    0.4%
   84     304.1     0.282    0.0%
   85     307.1     0.971    0.3%
   86     309.2     0.376    0.1%
   87     313.3     0.738    0.2%
   88     314.9     1.168    0.3%
   89     319.2     0.558    0.1%
   90     318.7     1.149    0.3%
   91     321.1     0.391    0.1%
   92     324.7     0.663    0.2%
   93     328.2     0.764    0.2%
   94     331.9     1.426    0.4%
   95     332.1     0.607    0.1%
   96     334.1     0.618    0.1%
   97     339.1     2.293    0.6%
   98     340.1     1.041    0.3%
   99     342.7     1.105    0.3%
  100     345.4      0.76    0.2%

Quality and confidence:
param     error
s         0.001

Model:
Time ~=    104.4
    + s    2.399
              µs

Reads = 11 + (0 * s)
Writes = 12 + (1 * s)
Pallet: "pallet_staking", Extrinsic: "new_era", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    287.2
    + n    51.72
              µs

Reads = 209 + (4 * v) + (4 * n)
Writes = 4 + (3 * v) + (0 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
    1   100      3907     10.93    0.2%
    2   100      4231     10.28    0.2%
    3   100      4414      15.1    0.3%
    4   100      4616     10.85    0.2%
    5   100      4949     9.781    0.1%
    6   100      5181     21.85    0.4%
    7   100      5560     18.47    0.3%
    8   100      5735     15.87    0.2%
    9   100      6198     10.18    0.1%
   10     1      1400     14.05    1.0%
   10     2      1448     7.546    0.5%
   10     3      1529     14.62    0.9%
   10     4      1585     13.17    0.8%
   10     5      1633     15.82    0.9%
   10     6      1678     14.18    0.8%
   10     7      1720     10.64    0.6%
   10     8      1785     14.53    0.8%
   10     9      1832     12.99    0.7%
   10    10      1890     5.413    0.2%
   10    11      1964     7.877    0.4%
   10    12      1998      13.4    0.6%
   10    13      2041     15.37    0.7%
   10    14      2089     17.06    0.8%
   10    15      2134     5.654    0.2%
   10    16      2192     10.33    0.4%
   10    17      2273     12.72    0.5%
   10    18      2320     14.96    0.6%
   10    19      2375     10.14    0.4%
   10    20      2401     12.71    0.5%
   10    21      2473     18.61    0.7%
   10    22      2508     10.27    0.4%
   10    23      2577     12.51    0.4%
   10    24      2644     6.834    0.2%
   10    25      2663      12.7    0.4%
   10    26      2726     13.13    0.4%
   10    27      2772     14.64    0.5%
   10    28      2852     9.635    0.3%
   10    29      2914     8.114    0.2%
   10    30      2957     11.53    0.3%
   10    31      2984     22.68    0.7%
   10    32      3074     13.04    0.4%
   10    33      3124     15.47    0.4%
   10    34      3185     24.49    0.7%
   10    35      3236     8.753    0.2%
   10    36      3256     10.43    0.3%
   10    37      3279     15.74    0.4%
   10    38      3374     14.66    0.4%
   10    39      3407     12.88    0.3%
   10    40      3476     11.14    0.3%
   10    41      3532     15.24    0.4%
   10    42      3534     8.183    0.2%
   10    43      3673     18.33    0.4%
   10    44      3645     10.64    0.2%
   10    45      3707     7.204    0.1%
   10    46      3741     14.47    0.3%
   10    47      3761      12.7    0.3%
   10    48      3880     15.99    0.4%
   10    49      3936     27.73    0.7%
   10    50      3974     10.92    0.2%
   10    51      3996     11.18    0.2%
   10    52      4077     14.01    0.3%
   10    53      4115     13.47    0.3%
   10    54      4163     20.08    0.4%
   10    55      4264     12.58    0.2%
   10    56      4277     14.65    0.3%
   10    57      4326     21.58    0.4%
   10    58      4423     25.48    0.5%
   10    59      4461     14.55    0.3%
   10    60      4496     11.99    0.2%
   10    61      4551      14.9    0.3%
   10    62      4587      19.3    0.4%
   10    63      4666     20.64    0.4%
   10    64      4746     11.95    0.2%
   10    65      4791      10.9    0.2%
   10    66      4839      20.3    0.4%
   10    67      4884     10.28    0.2%
   10    68      4905     13.07    0.2%
   10    69      4940      15.8    0.3%
   10    70      5017     18.57    0.3%
   10    71      5021     16.84    0.3%
   10    72      5159     11.14    0.2%
   10    73      5189      10.9    0.2%
   10    74      5187     19.97    0.3%
   10    75      5295     10.77    0.2%
   10    76      5347     10.88    0.2%
   10    77      5385     15.03    0.2%
   10    78      5404     21.04    0.3%
   10    79      5464     11.57    0.2%
   10    80      5536     13.18    0.2%
   10    81      5580      22.1    0.3%
   10    82      5649      9.19    0.1%
   10    83      5664     15.83    0.2%
   10    84      5686     11.96    0.2%
   10    85      5756      10.5    0.1%
   10    86      5770     19.52    0.3%
   10    87      5910     11.68    0.1%
   10    88      5893      24.2    0.4%
   10    89      5988     10.84    0.1%
   10    90      6061     10.22    0.1%
   10    91      5992     28.85    0.4%
   10    92      6197      38.4    0.6%
   10    93      6168     27.33    0.4%
   10    94      6201     14.47    0.2%
   10    95      6315     22.88    0.3%
   10    96      6356     17.44    0.2%
   10    97      6402     10.46    0.1%
   10    98      6396     10.85    0.1%
   10    99      6464     11.75    0.1%
   10   100      6480     22.77    0.3%

Quality and confidence:
param     error
v          0.95
n         0.047

Model:
Time ~=        0
    + v    304.5
    + n    51.44
              µs

Reads = 209 + (4 * v) + (4 * n)
Writes = 4 + (3 * v) + (0 * n)
Pallet: "pallet_staking", Extrinsic: "get_npos_voters", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    25.13
    + n    33.74
    + s    22.12
              µs

Reads = 201 + (3 * v) + (4 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n     s   mean µs  sigma µs       %
  500  1000    20     43710     110.8    0.2%
  510  1000    20     44380     88.16    0.1%
  520  1000    20     44690     225.4    0.5%
  530  1000    20     45140     127.7    0.2%
  540  1000    20     45450     130.9    0.2%
  550  1000    20     45730     221.9    0.4%
  560  1000    20     45830     126.5    0.2%
  570  1000    20     45720     195.6    0.4%
  580  1000    20     46250     233.9    0.5%
  590  1000    20     46150     170.6    0.3%
  600  1000    20     46500     109.9    0.2%
  610  1000    20     46650     149.1    0.3%
  620  1000    20     47250     260.2    0.5%
  630  1000    20     46820     119.2    0.2%
  640  1000    20     47720     168.2    0.3%
  650  1000    20     47500     236.8    0.4%
  660  1000    20     47580       173    0.3%
  670  1000    20     47700     163.4    0.3%
  680  1000    20     48650     116.1    0.2%
  690  1000    20     49250     149.4    0.3%
  700  1000    20     48500     203.3    0.4%
  710  1000    20     49340     162.9    0.3%
  720  1000    20     49720     99.88    0.2%
  730  1000    20     49510     241.4    0.4%
  740  1000    20     49900     158.1    0.3%
  750  1000    20     50040     150.4    0.3%
  760  1000    20     50320     217.5    0.4%
  770  1000    20     51180     200.8    0.3%
  780  1000    20     51100     106.3    0.2%
  790  1000    20     51220     373.2    0.7%
  800  1000    20     51840     221.8    0.4%
  810  1000    20     51760       221    0.4%
  820  1000    20     52050     131.2    0.2%
  830  1000    20     51510     160.9    0.3%
  840  1000    20     52530     215.5    0.4%
  850  1000    20     52530     193.6    0.3%
  860  1000    20     53030     394.2    0.7%
  870  1000    20     53530     202.9    0.3%
  880  1000    20     53570     131.6    0.2%
  890  1000    20     53660     182.3    0.3%
  900  1000    20     54050     242.5    0.4%
  910  1000    20     54580     146.4    0.2%
  920  1000    20     54690     174.6    0.3%
  930  1000    20     55110     199.2    0.3%
  940  1000    20     54760     150.2    0.2%
  950  1000    20     55440     274.9    0.4%
  960  1000    20     55530     275.2    0.4%
  970  1000    20     55530     363.3    0.6%
  980  1000    20     56220     227.1    0.4%
  990  1000    20     56360     284.3    0.5%
 1000   500    20     39400     162.5    0.4%
 1000   510    20     40120     212.7    0.5%
 1000   520    20     40820     120.5    0.2%
 1000   530    20     40910     245.5    0.6%
 1000   540    20     40940     101.3    0.2%
 1000   550    20     41590     123.7    0.2%
 1000   560    20     41660     103.1    0.2%
 1000   570    20     41690       242    0.5%
 1000   580    20     42370     142.2    0.3%
 1000   590    20     42440     208.2    0.4%
 1000   600    20     42540     87.09    0.2%
 1000   610    20     43240     84.27    0.1%
 1000   620    20     43410     153.6    0.3%
 1000   630    20     43940     94.37    0.2%
 1000   640    20     44600     175.3    0.3%
 1000   650    20     44460     134.1    0.3%
 1000   660    20     45000     153.9    0.3%
 1000   670    20     45560     181.4    0.3%
 1000   680    20     45900     74.16    0.1%
 1000   690    20     46060       123    0.2%
 1000   700    20     46370     155.5    0.3%
 1000   710    20     46920     100.7    0.2%
 1000   720    20     47010     148.6    0.3%
 1000   730    20     47200     203.5    0.4%
 1000   740    20     47930     103.4    0.2%
 1000   750    20     48240     109.5    0.2%
 1000   760    20     47900     169.1    0.3%
 1000   770    20     48950     127.7    0.2%
 1000   780    20     48800     289.4    0.5%
 1000   790    20     49460     153.5    0.3%
 1000   800    20     49920     109.6    0.2%
 1000   810    20     50350     247.1    0.4%
 1000   820    20     50070     281.4    0.5%
 1000   830    20     50910     250.3    0.4%
 1000   840    20     51360     201.5    0.3%
 1000   850    20     51700     310.1    0.5%
 1000   860    20     51740     141.1    0.2%
 1000   870    20     52180     218.8    0.4%
 1000   880    20     52470     187.1    0.3%
 1000   890    20     52620       114    0.2%
 1000   900    20     53070     202.1    0.3%
 1000   910    20     54020     138.7    0.2%
 1000   920    20     53600     122.1    0.2%
 1000   930    20     53560     238.3    0.4%
 1000   940    20     53600       224    0.4%
 1000   950    20     54350     200.1    0.3%
 1000   960    20     54660     230.7    0.4%
 1000   970    20     55620       214    0.3%
 1000   980    20     55280     157.5    0.2%
 1000   990    20     57390       242    0.4%
 1000  1000     1     57150     129.3    0.2%
 1000  1000     2     56150     298.9    0.5%
 1000  1000     3     56120     101.6    0.1%
 1000  1000     4     57430     260.5    0.4%
 1000  1000     5     57040     156.9    0.2%
 1000  1000     6     56560     178.6    0.3%
 1000  1000     7     56940     180.6    0.3%
 1000  1000     8     56570     288.9    0.5%
 1000  1000     9     57200     268.5    0.4%
 1000  1000    10     56250     239.2    0.4%
 1000  1000    11     56980     196.2    0.3%
 1000  1000    12     56380     338.2    0.6%
 1000  1000    13     57260     137.1    0.2%
 1000  1000    14     57220     130.6    0.2%
 1000  1000    15     57780     146.8    0.2%
 1000  1000    16     57480       270    0.4%
 1000  1000    17     57050     78.48    0.1%
 1000  1000    18     57690     172.7    0.2%
 1000  1000    19     56710     240.7    0.4%
 1000  1000    20     56910     200.6    0.3%

Quality and confidence:
param     error
v         0.094
n         0.094
s         3.201

Model:
Time ~=        0
    + v    25.27
    + n    34.12
    + s        0
              µs

Reads = 201 + (3 * v) + (4 * n) + (1 * s)
Writes = 0 + (0 * v) + (0 * n) + (0 * s)
Pallet: "pallet_staking", Extrinsic: "get_npos_targets", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    11.71
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v   mean µs  sigma µs       %
  500      5761     34.84    0.6%
  510      5642     29.08    0.5%
  520      5936     42.28    0.7%
  530      6062     27.46    0.4%
  540      6100     21.28    0.3%
  550      6146      28.8    0.4%
  560      6425     45.32    0.7%
  570      6427     47.02    0.7%
  580      6596     34.43    0.5%
  590      6709     59.64    0.8%
  600      6924     22.98    0.3%
  610      6830        17    0.2%
  620      7220     31.47    0.4%
  630      7182     79.01    1.1%
  640      7160     37.88    0.5%
  650      7608     49.11    0.6%
  660      7449      62.3    0.8%
  670      7766     44.89    0.5%
  680      7788        40    0.5%
  690      7938     41.34    0.5%
  700      7932     43.42    0.5%
  710      8111      60.8    0.7%
  720      8243     53.84    0.6%
  730      8332     43.71    0.5%
  740      8485     38.32    0.4%
  750      8651     35.87    0.4%
  760      8821     45.97    0.5%
  770      8823     48.86    0.5%
  780      8949     57.89    0.6%
  790      9142     37.59    0.4%
  800      9158     57.55    0.6%
  810      9134      54.2    0.5%
  820      9496     64.13    0.6%
  830      9374     47.86    0.5%
  840      9617     46.05    0.4%
  850      9775     89.77    0.9%
  860      9857     51.95    0.5%
  870      9917     60.84    0.6%
  880     10140     74.19    0.7%
  890     10150     55.94    0.5%
  900     10460      52.6    0.5%
  910     10270     45.24    0.4%
  920     10580     82.88    0.7%
  930     10550     42.84    0.4%
  940     10750     57.66    0.5%
  950     10990     61.19    0.5%
  960     10980     78.78    0.7%
  970     11210     76.86    0.6%
  980     11350     90.47    0.7%
  990     11630     48.08    0.4%
 1000     11590     80.77    0.6%

Quality and confidence:
param     error
v         0.031

Model:
Time ~=        0
    + v    11.72
              µs

Reads = 1 + (1 * v)
Writes = 0 + (0 * v)
Pallet: "pallet_staking", Extrinsic: "set_staking_limits", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6.56
              µs

Reads = 0
Writes = 5
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=     6.56
              µs

Reads = 0
Writes = 5
Pallet: "pallet_staking", Extrinsic: "chill_other", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=    91.74
              µs

Reads = 11
Writes = 6
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=    91.74
              µs

Reads = 11
Writes = 6
Pallet: "pallet_staking", Extrinsic: "rebag", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=      106
              µs

Reads = 9
Writes = 7
Min Squares Analysis
========
-- Extrinsic Time --

Model:
Time ~=      106
              µs

Reads = 9
Writes = 7
Pallet: "pallet_staking", Extrinsic: "regenerate", Lowest values: [], Highest values: [], Steps: [50], Repeat: 20
Median Slopes Analysis
========
-- Extrinsic Time --

Model:
Time ~=        0
    + v    42.46
    + n    44.42
              µs

Reads = 2 + (3 * v) + (3 * n)
Writes = 2 + (2 * v) + (2 * n)
Min Squares Analysis
========
-- Extrinsic Time --

Data points distribution:
    v     n   mean µs  sigma µs       %
  500  1000     61770     113.9    0.1%
  510  1000     62180     192.6    0.3%
  520  1000     62760     86.23    0.1%
  530  1000     62880     252.1    0.4%
  540  1000     63420       152    0.2%
  550  1000     63790     124.3    0.1%
  560  1000     64590     99.41    0.1%
  570  1000     64640     248.7    0.3%
  580  1000     66130     189.3    0.2%
  590  1000     65730     218.3    0.3%
  600  1000     65710     146.5    0.2%
  610  1000     66690     257.7    0.3%
  620  1000     66980     179.9    0.2%
  630  1000     67000     255.6    0.3%
  640  1000     68360     176.7    0.2%
  650  1000     68620     182.5    0.2%
  660  1000     68870     199.3    0.2%
  670  1000     69000     158.2    0.2%
  680  1000     69220     208.5    0.3%
  690  1000     70400     239.5    0.3%
  700  1000     70810     179.1    0.2%
  710  1000     71570     92.21    0.1%
  720  1000     71150     144.8    0.2%
  730  1000     71630     197.2    0.2%
  740  1000     72030     100.4    0.1%
  750  1000     72310     153.8    0.2%
  760  1000     72710     350.1    0.4%
  770  1000     73230     452.5    0.6%
  780  1000     72920     130.3    0.1%
  790  1000     74010     239.2    0.3%
  800  1000     74130     180.5    0.2%
  810  1000     74330     294.8    0.3%
  820  1000     75330     283.9    0.3%
  830  1000     76260       136    0.1%
  840  1000     76680     194.9    0.2%
  850  1000     76350     205.5    0.2%
  860  1000     77650     330.3    0.4%
  870  1000     77270     191.5    0.2%
  880  1000     78410     278.1    0.3%
  890  1000     77810     417.4    0.5%
  900  1000     78930       211    0.2%
  910  1000     79220     273.8    0.3%
  920  1000     80080     184.5    0.2%
  930  1000     80150       464    0.5%
  940  1000     80430     260.7    0.3%
  950  1000     81250     221.1    0.2%
  960  1000     80670     225.6    0.2%
  970  1000     81730     240.3    0.2%
  980  1000     82600     125.7    0.1%
  990  1000     82780     181.8    0.2%
 1000   500     60940     129.1    0.2%
 1000   510     60830     146.5    0.2%
 1000   520     61700     153.5    0.2%
 1000   530     61930     186.7    0.3%
 1000   540     62840     106.9    0.1%
 1000   550     62920     265.7    0.4%
 1000   560     63680     289.5    0.4%
 1000   570     63880     171.3    0.2%
 1000   580     64590     113.1    0.1%
 1000   590     64870     169.4    0.2%
 1000   600     65550     164.6    0.2%
 1000   610     65570     147.2    0.2%
 1000   620     65670       215    0.3%
 1000   630     66660     80.73    0.1%
 1000   640     67200     238.1    0.3%
 1000   650     67140     167.3    0.2%
 1000   660     68290     168.3    0.2%
 1000   670     69190     306.2    0.4%
 1000   680     69520     178.4    0.2%
 1000   690     68550     205.1    0.2%
 1000   700     69300     148.2    0.2%
 1000   710     70160     128.2    0.1%
 1000   720     71040     140.6    0.1%
 1000   730     71130     192.9    0.2%
 1000   740     71950     97.74    0.1%
 1000   750     71530     227.2    0.3%
 1000   760     71570     98.85    0.1%
 1000   770     73020     219.9    0.3%
 1000   780     72130     105.1    0.1%
 1000   790     72930     203.8    0.2%
 1000   800     74330     242.2    0.3%
 1000   810     74520     175.9    0.2%
 1000   820     75370     313.2    0.4%
 1000   830     76000     198.7    0.2%
 1000   840     75630     260.2    0.3%
 1000   850     76030     181.1    0.2%
 1000   860     77480     176.1    0.2%
 1000   870     76640     230.4    0.3%
 1000   880     77640     94.92    0.1%
 1000   890     78710     136.1    0.1%
 1000   900     78430     300.6    0.3%
 1000   910     80270       262    0.3%
 1000   920     79220     258.4    0.3%
 1000   930     80670       215    0.2%
 1000   940     79230     264.9    0.3%
 1000   950     80920       194    0.2%
 1000   960     81410     233.8    0.2%
 1000   970     80860     280.4    0.3%
 1000   980     81910     284.5    0.3%
 1000   990     82500     220.8    0.2%
 1000  1000     83250       284    0.3%

Quality and confidence:
param     error
v         0.115
n         0.115

Model:
Time ~=        0
    + v    42.24
    + n    44.43
              µs

Reads = 2 + (3 * v) + (3 * n)
Writes = 2 + (2 * v) + (2 * n)

…path=bin/node/cli/Cargo.toml -- benchmark --chain=dev --steps=50 --repeat=20 --pallet=pallet_staking --extrinsic=* --execution=wasm --wasm-execution=compiled --heap-pages=4096 --output=./frame/staking/src/weights.rs --template=./.maintain/frame-weight-template.hbs
let src2_node = Node::<T>::from_id(&src2_stash).ok_or("node not found for src stash")?;
let weight_of = Staking::<T>::weight_of_fn();
ensure!(
!src2_node.is_misplaced(&weight_of),
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let's not forget that we can get rid of weight_of_fn in this API

Comment on lines +214 to +215
// - The destination bag is not empty, because then we need to update the `next` pointer
// of the previous node in addition to the work we do otherwise.
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Suggested change
// - The destination bag is not empty, because then we need to update the `next` pointer
// of the previous node in addition to the work we do otherwise.
// - The destination must also be such that the new node is inserted in between two other nodes (say, `A` and `B`), so that the `next` of `A` and `prev` of `B` is updated.

is this what you mean?

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no - whenever we insert a node into a bag we always insert it as a tail, so we only update the next of the "old" tail to point at the node being inserted.

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While we've learned a good amount from the outcome here, I think we should freeze this and first move the bags stuff into its own pallet. I've discussed it also with @shawntabrizi and we're both quite positive on the idea.

We can put on ice and pick this up again once the transition is done.

emostov and others added 2 commits August 1, 2021 11:49
Co-authored-by: Kian Paimani <5588131+kianenigma@users.noreply.github.com>
Co-authored-by: Kian Paimani <5588131+kianenigma@users.noreply.github.com>
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2 participants