Hy/plpython3 #2
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beeender
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Apr 18, 2022
src/pl/plpython/plpy_main.c
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| /* GUC variables */ | ||
| #if PY_MAJOR_VERSION >= 3 | ||
| char *plpython3_path = NULL; |
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make it static, it should not be used out of this file.
static char *plpython3_path = NULL;
src/pl/plpython/plpy_main.c
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| bool | ||
| plpython3_check_python_path(char **newval, void **extra, GucSource source) { | ||
| if (PLy_path_added) |
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I still don't understand why cannot we use inited.
Even user sets it twice, as long as PLy_initialize has not been executed, it doesn't take effect yet.
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because I think the logic is user may not create plpython3u language or call the function.
they just load plython3u then the inited can not access
src/pl/plpython/plpy_main.c
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| plpython3_check_python_path(char **newval, void **extra, GucSource source) { | ||
| if (PLy_path_added) | ||
| { | ||
| GUC_check_errmsg("SET PYTHONPATH for plpython3 can only set once in one session"); |
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If the above can be changed, then we need to modify this message.
src/pl/plpython/plpy_main.c
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| GUC_check_errmsg("SET PYTHONPATH for plpython3 can only set once in one session"); | ||
| return false; | ||
| } | ||
| if (strcmp(*newval, "") != 0) |
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if we have this check, then the PLy_path_added is not needed. Since we can always check if the plpython3_path is NULL. Right?
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not for sure we need to make the default value empty string otherwise will cause the error (definecostumstring can not default NULL).
src/pl/plpython/plpy_main.c
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| else | ||
| unsetenv("PYTHONPATH"); | ||
| #endif | ||
| unsetenv("PYTHONHOME"); |
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I am not quite sure if there is anyone relies on the PYTHONHOME for plpython2 for now. Probably it will be safer to have this for python3 only.
beeender
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Apr 18, 2022
beeender
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Apr 19, 2022
beeender
approved these changes
Apr 20, 2022
src/pl/plpython/plpy_main.c
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| @@ -137,6 +156,18 @@ _PG_init(void) | |||
| prev_cancel_pending_hook = cancel_pending_hook; | |||
| cancel_pending_hook = PLy_handle_cancel_interrupt; | |||
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| #if PY_MAJOR_VERSION >= 3 | |||
| DefineCustomStringVariable("plpython3.python_path", | |||
| gettext_noop("Python path for plpython3."), | |||
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last comment :
'PYTHONPATH' for plpython3 will be clearer IMO.
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beeender
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May 24, 2022
…CREATE/ALTER resouce group. In some scenarios, the AccessExclusiveLock for table pg_resgroupcapability may cause database setup/recovery pending. Below is why we need change the AccessExclusiveLock to ExclusiveLock. This lock on table pg_resgroupcapability is used to concurrent update this table when run "Create/Alter resource group" statement. There is a CPU limit, after modify one resource group, it has to check if the whole CPU usage of all resource groups doesn't exceed 100%. Before this fix, AccessExclusiveLock is used. Suppose one user is running "Alter resource group" statement, QD will dispatch this statement to all QEs, so it is a two phase commit(2PC) transaction. When QD dispatched "Alter resource group" statement and QE acquire the AccessExclusiveLock for table pg_resgroupcapability. Until the 2PC distributed transaction committed, QE can release the AccessExclusiveLock for this table. In the second phase, QD will call function doNotifyingCommitPrepared to broadcast "commit prepared" command to all QEs, QE has already finish prepared, this transation is a prepared transaction. Suppose at this point, there is a primary segment down and a mirror will be promoted to primary. The mirror got the "promoted" message from coordinator, and will recover based on xlog from primary, in order to recover the prepared transaction, it will read the prepared transaction log entry and acquire AccessExclusiveLock for table pg_resgroupcapability. The callstack is: #0 lock_twophase_recover (xid=, info=, recdata=, len=) at lock.c:4697 #1 ProcessRecords (callbacks=, xid=2933, bufptr=0x1d575a8 "") at twophase.c:1757 #2 RecoverPreparedTransactions () at twophase.c:2214 #3 StartupXLOG () at xlog.c:8013 #4 StartupProcessMain () at startup.c:231 #5 AuxiliaryProcessMain (argc=argc@entry=2, argv=argv@entry=0x7fff84b94a70) at bootstrap.c:459 #6 StartChildProcess (type=StartupProcess) at postmaster.c:5917 #7 PostmasterMain (argc=argc@entry=7, argv=argv@entry=0x1d555b0) at postmaster.c:1581 #8 main (argc=7, argv=0x1d555b0) at main.c:240 After that, the database instance will start up, all related initialization functions will be called. However, there is a function named "InitResGroups", it will acquire AccessShareLock for table pg_resgroupcapability and do some initialization stuff. The callstack is: #6 WaitOnLock (locallock=locallock@entry=0x1c7f248, owner=owner@entry=0x1ca0a40) at lock.c:1999 #7 LockAcquireExtended (locktag=locktag@entry=0x7ffd15d18d90, lockmode=lockmode@entry=1, sessionLock=sessionLock@entry=false, dontWait=dontWait@entry=false, reportMemoryError=reportMemoryError@entry=true, locallockp=locallockp@entry=0x7ffd15d18d88) at lock.c:1192 #8 LockRelationOid (relid=6439, lockmode=1) at lmgr.c:126 #9 relation_open (relationId=relationId@entry=6439, lockmode=lockmode@entry=1) at relation.c:56 #10 table_open (relationId=relationId@entry=6439, lockmode=lockmode@entry=1) at table.c:47 #11 InitResGroups () at resgroup.c:581 #12 InitResManager () at resource_manager.c:83 #13 initPostgres (in_dbname=, dboid=dboid@entry=0, username=username@entry=0x1c5b730 "linw", useroid=useroid@entry=0, out_dbname=out_dbname@entry=0x0, override_allow_connections=override_allow_connections@entry=false) at postinit.c:1284 #14 PostgresMain (argc=1, argv=argv@entry=0x1c8af78, dbname=0x1c89e70 "postgres", username=0x1c5b730 "linw") at postgres.c:4812 #15 BackendRun (port=, port=) at postmaster.c:4922 #16 BackendStartup (port=0x1c835d0) at postmaster.c:4607 #17 ServerLoop () at postmaster.c:1963 #18 PostmasterMain (argc=argc@entry=7, argv=argv@entry=0x1c595b0) at postmaster.c:1589 #19 in main (argc=7, argv=0x1c595b0) at main.c:240 The AccessExclusiveLock is not released, and it is not compatible with any other locks, so the startup process will be pending on this lock. So the mirror can't become primary successfully. Even users run "gprecoverseg" to recover the primary segment. the result is similar. The primary segment will recover from xlog, it will recover prepared transactions and acquire AccessExclusiveLock for table pg_resgroupcapability. Then the startup process is pending on this lock. Unless users change the resource type to "queue", the function InitResGroups will not be called, and won't be blocked, then the primary segment can startup normally. After this fix, ExclusiveLock is acquired when alter resource group. In above case, the startup process acquires AccessShareLock, ExclusiveLock and AccessShareLock are compatible. The startup process can run successfully. After startup, QE will get RECOVERY_COMMIT_PREPARED command from QD, it will finish the second phase of this distributed transaction and release ExclusiveLock on table pg_resgroupcapability. The callstack is: #0 lock_twophase_postcommit (xid=, info=, recdata=0x3303458, len=) at lock.c:4758 #1 ProcessRecords (callbacks=, xid=, bufptr=0x3303458 "") at twophase.c:1757 #2 FinishPreparedTransaction (gid=gid@entry=0x323caf5 "25", isCommit=isCommit@entry=true, raiseErrorIfNotFound=raiseErrorIfNotFound@entry=false) at twophase.c:1704 #3 in performDtxProtocolCommitPrepared (gid=gid@entry=0x323caf5 "25", raiseErrorIfNotFound=raiseErrorIfNotFound@entry=false) at cdbtm.c:2107 #4 performDtxProtocolCommand (dtxProtocolCommand=dtxProtocolCommand@entry=DTX_PROTOCOL_COMMAND_RECOVERY_COMMIT_PREPARED, gid=gid@entry=0x323caf5 "25", contextInfo=contextInfo@entry=0x10e1820 ) at cdbtm.c:2279 #5 exec_mpp_dtx_protocol_command (contextInfo=0x10e1820 , gid=0x323caf5 "25", loggingStr=0x323cad8 "Recovery Commit Prepared", dtxProtocolCommand=DTX_PROTOCOL_COMMAND_RECOVERY_COMMIT_PREPARED) at postgres.c:1570 #6 PostgresMain (argc=, argv=argv@entry=0x3268f98, dbname=0x3267e90 "postgres", username=) at postgres.c:5482 The test case of this commit simulates a repro of this bug.
beeender
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May 24, 2022
…ce (#12447)
Recently I built from GreenPlum master branch to run TPC-DS query with 1GB data. For Q47 and Q57, when I turned off GUC `execute_pruned_plan` (on by default), some of worker processes will be hang and the query never returns.
Take Q57 as an example. My cluster configuration is 1 QD + 2 QE. The query looks like:
```sql
with v1 as(
select
i_category,i_brand,
cc_name,d_year,d_moy,
sum(cs_sales_price) sum_sales,
avg(sum(cs_sales_price)) over (partition by
i_category,i_brand,cc_name,d_year)
avg_monthly_sales,
rank() over (partition by
i_category,i_brand,cc_name
order by
d_year,d_moy
) rn
from
item,catalog_sales,date_dim,call_center
where
cs_item_sk = i_item_sk and
cs_sold_date_sk = d_date_sk and
cc_call_center_sk= cs_call_center_sk and(
d_year = 1999 or
( d_year = 1999-1 and d_moy =12) or
( d_year = 1999+1 and d_moy =1)
)
group by
i_category,i_brand,cc_name,d_year,d_moy
),
v2 as(
select
v1.i_category,v1.i_brand,v1.cc_name,
v1.d_year,v1.d_moy,v1.avg_monthly_sales,
v1.sum_sales,v1_lag.sum_sales psum,
v1_lead.sum_sales nsum
from
v1,v1 v1_lag,v1 v1_lead
where
v1.i_category = v1_lag.i_category and
v1.i_category = v1_lead.i_category and
v1.i_brand = v1_lag.i_brand and
v1.i_brand = v1_lead.i_brand and
v1. cc_name = v1_lag. cc_name and
v1. cc_name = v1_lead. cc_name and
v1.rn = v1_lag.rn + 1 and
v1.rn = v1_lead.rn - 1
)
select *
from v2
where
d_year = 1999 and
avg_monthly_sales > 0 and
case when avg_monthly_sales > 0 then
abs(sum_sales - avg_monthly_sales) / avg_monthly_sales
else null end > 0.1
order by
sum_sales - avg_monthly_sales,3
limit 100;
```
When `execute_pruned_plan` is on by default, the plan looks like:
```
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Result (cost=0.00..2832.84 rows=1 width=64) (actual time=10792.606..10792.702 rows=100 loops=1)
-> Gather Motion 2:1 (slice1; segments: 2) (cost=0.00..2832.84 rows=1 width=64) (actual time=10792.597..10792.673 rows=100 loops=1)
Merge Key: ((share0_ref4.sum_sales - share0_ref4.avg_monthly_sales)), share0_ref4.cc_name
-> Sort (cost=0.00..2832.84 rows=1 width=72) (actual time=10791.203..10791.225 rows=50 loops=1)
Sort Key: ((share0_ref4.sum_sales - share0_ref4.avg_monthly_sales)), share0_ref4.cc_name
Sort Method: quicksort Memory: 152kB
-> Sequence (cost=0.00..2832.84 rows=1 width=72) (actual time=10790.522..10790.559 rows=50 loops=1)
-> Shared Scan (share slice:id 1:0) (cost=0.00..1539.83 rows=1 width=1) (actual time=10140.895..10145.397 rows=16510 loops=1)
-> WindowAgg (cost=0.00..1539.83 rows=1 width=56) (actual time=10082.465..10128.750 rows=16510 loops=1)
Partition By: item.i_category, item.i_brand, call_center.cc_name
Order By: date_dim.d_year, date_dim.d_moy
-> Sort (cost=0.00..1539.83 rows=1 width=48) (actual time=10082.429..10084.923 rows=16510 loops=1)
Sort Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year, date_dim.d_moy
Sort Method: quicksort Memory: 20078kB
-> Redistribute Motion 2:2 (slice2; segments: 2) (cost=0.00..1539.83 rows=1 width=48) (actual time=9924.269..9989.657 rows=16510 loops=1)
Hash Key: item.i_category, item.i_brand, call_center.cc_name
-> WindowAgg (cost=0.00..1539.83 rows=1 width=48) (actual time=9924.717..9974.500 rows=16633 loops=1)
Partition By: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year
-> Sort (cost=0.00..1539.83 rows=1 width=126) (actual time=9924.662..9927.280 rows=16633 loops=1)
Sort Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year
Sort Method: quicksort Memory: 20076kB
-> Redistribute Motion 2:2 (slice3; segments: 2) (cost=0.00..1539.83 rows=1 width=126) (actual time=9394.220..9856.375 rows=16633 loops=1)
Hash Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year
-> GroupAggregate (cost=0.00..1539.83 rows=1 width=126) (actual time=9391.783..9833.988 rows=16424 loops=1)
Group Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year, date_dim.d_moy
-> Sort (cost=0.00..1539.83 rows=1 width=124) (actual time=9397.448..9628.606 rows=174584 loops=1)
Sort Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year, date_dim.d_moy
Sort Method: external merge Disk: 134144kB
-> Redistribute Motion 2:2 (slice4; segments: 2) (cost=0.00..1539.83 rows=1 width=124) (actual time=6107.447..8237.581 rows=174584 loops=1)
Hash Key: item.i_category, item.i_brand, call_center.cc_name, date_dim.d_year, date_dim.d_moy
-> Hash Join (cost=0.00..1539.83 rows=1 width=124) (actual time=6112.706..7088.349 rows=178669 loops=1)
Hash Cond: (date_dim.d_date_sk = catalog_sales.cs_sold_date_sk)
-> Seq Scan on date_dim (cost=0.00..436.38 rows=204 width=12) (actual time=10.656..17.972 rows=222 loops=1)
Filter: ((d_year = 1999) OR ((d_year = 1998) AND (d_moy = 12)) OR ((d_year = 2000) AND (d_moy = 1)))
Rows Removed by Filter: 36504
-> Hash (cost=1103.41..1103.41 rows=1 width=120) (actual time=6100.040..6100.040 rows=1430799 loops=1)
Buckets: 16384 (originally 16384) Batches: 32 (originally 1) Memory Usage: 12493kB
-> Broadcast Motion 2:2 (slice5; segments: 2) (cost=0.00..1103.41 rows=1 width=120) (actual time=1.802..5410.377 rows=1434428 loops=1)
-> Nested Loop (cost=0.00..1103.40 rows=1 width=120) (actual time=1.632..5127.625 rows=718766 loops=1)
Join Filter: true
-> Redistribute Motion 2:2 (slice6; segments: 2) (cost=0.00..1097.40 rows=1 width=22) (actual time=1.564..362.958 rows=718766 loops=1)
Hash Key: catalog_sales.cs_item_sk
-> Hash Join (cost=0.00..1097.40 rows=1 width=22) (actual time=1.112..996.643 rows=717589 loops=1)
Hash Cond: (catalog_sales.cs_call_center_sk = call_center.cc_call_center_sk)
-> Seq Scan on catalog_sales (cost=0.00..509.10 rows=720774 width=18) (actual time=0.144..602.362 rows=721193 loops=1)
-> Hash (cost=431.00..431.00 rows=1 width=12) (actual time=0.022..0.022 rows=6 loops=1)
Buckets: 32768 Batches: 1 Memory Usage: 257kB
-> Broadcast Motion 2:2 (slice7; segments: 2) (cost=0.00..431.00 rows=1 width=12) (actual time=0.009..0.012 rows=6 loops=1)
-> Seq Scan on call_center (cost=0.00..431.00 rows=1 width=12) (actual time=0.032..0.035 rows=4 loops=1)
-> Index Scan using item_pkey on item (cost=0.00..6.00 rows=1 width=102) (actual time=0.000..0.006 rows=1 loops=718766)
Index Cond: (i_item_sk = catalog_sales.cs_item_sk)
-> Redistribute Motion 1:2 (slice8) (cost=0.00..1293.01 rows=1 width=72) (actual time=646.614..646.646 rows=50 loops=1)
-> Limit (cost=0.00..1293.01 rows=1 width=72) (actual time=10787.533..10787.700 rows=100 loops=1)
-> Gather Motion 2:1 (slice9; segments: 2) (cost=0.00..1293.01 rows=1 width=72) (actual time=10787.527..10787.654 rows=100 loops=1)
Merge Key: ((share0_ref4.sum_sales - share0_ref4.avg_monthly_sales)), share0_ref4.cc_name
-> Sort (cost=0.00..1293.01 rows=1 width=72) (actual time=10789.933..10789.995 rows=357 loops=1)
Sort Key: ((share0_ref4.sum_sales - share0_ref4.avg_monthly_sales)), share0_ref4.cc_name
Sort Method: quicksort Memory: 14998kB
-> Result (cost=0.00..1293.01 rows=1 width=150) (actual time=10648.280..10774.898 rows=12379 loops=1)
Filter: ((share0_ref4.d_year = 1999) AND (share0_ref4.avg_monthly_sales > '0'::numeric) AND (CASE WHEN (share0_ref4.avg_monthly_sales > '0'::numeric) THEN (abs((share0_ref4.sum_sales - share0_ref4.avg_monthly_sales)) / share0_ref4.avg_monthly_sales) ELSE NULL::numeric END > 0.1))
-> Hash Join (cost=0.00..1293.01 rows=1 width=150) (actual time=10648.253..10740.262 rows=13582 loops=1)
Hash Cond: ((share0_ref4.i_category = share0_ref3.i_category) AND (share0_ref4.i_brand = share0_ref3.i_brand) AND ((share0_ref4.cc_name)::text = (share0_ref3.cc_name)::text) AND (share0_ref4.rn = (share0_ref3.rn + 1)) AND (share0_ref4.rn = (share0_ref2.rn - 1)))
-> Shared Scan (share slice:id 9:0) (cost=0.00..431.00 rows=1 width=142) (actual time=0.013..5.570 rows=16510 loops=1)
-> Hash (cost=862.00..862.00 rows=1 width=142) (actual time=10647.380..10647.380 rows=209076 loops=1)
Buckets: 65536 (originally 32768) Batches: 2 (originally 1) Memory Usage: 31389kB
-> Hash Join (cost=0.00..862.00 rows=1 width=142) (actual time=10156.494..10374.421 rows=209076 loops=1)
Hash Cond: ((share0_ref3.i_category = share0_ref2.i_category) AND (share0_ref3.i_brand = share0_ref2.i_brand) AND ((share0_ref3.cc_name)::text = (share0_ref2.cc_name)::text))
-> Shared Scan (share slice:id 9:0) (cost=0.00..431.00 rows=1 width=126) (actual time=0.009..6.887 rows=16510 loops=1)
-> Hash (cost=431.00..431.00 rows=1 width=126) (actual time=10156.297..10156.298 rows=16178 loops=1)
Buckets: 32768 Batches: 1 Memory Usage: 3144kB
-> Shared Scan (share slice:id 9:0) (cost=0.00..431.00 rows=1 width=126) (actual time=10139.421..10144.473 rows=16510 loops=1)
Planning Time: 1905.667 ms
(slice0) Executor memory: 330K bytes.
(slice1) Executor memory: 4750K bytes avg x 2 workers, 4968K bytes max (seg1). Work_mem: 4861K bytes max.
(slice2) Executor memory: 4701K bytes avg x 2 workers, 4952K bytes max (seg0). Work_mem: 4894K bytes max.
(slice3) Executor memory: 12428K bytes avg x 2 workers, 12428K bytes max (seg0). Work_mem: 12375K bytes max.
* (slice4) Executor memory: 14021K bytes avg x 2 workers, 14021K bytes max (seg0). Work_mem: 12493K bytes max, 221759K bytes wanted.
(slice5) Executor memory: 77K bytes avg x 2 workers, 77K bytes max (seg0).
(slice6) Executor memory: 323K bytes avg x 2 workers, 323K bytes max (seg0). Work_mem: 257K bytes max.
(slice7) Executor memory: 39K bytes avg x 2 workers, 39K bytes max (seg0).
(slice8) Executor memory: 242K bytes (entry db).
* (slice9) Executor memory: 35344K bytes avg x 2 workers, 35360K bytes max (seg1). Work_mem: 31389K bytes max, 37501K bytes wanted.
Memory used: 128000kB
Memory wanted: 3328681kB
Optimizer: Pivotal Optimizer (GPORCA)
Execution Time: 10856.507 ms
(86 rows)
Time: 12779.991 ms (00:12.780)
```
There is only one share slice in this query, one producer in slice 1, three consumers in slice 9. However, when I turned GUC off, the query never returns, and the process situation looks like:
```
postgres 22285 22255 0 03:03 pts/1 00:00:00 psql -p9221
postgres 22288 20912 3 03:03 ? 00:00:03 postgres: 9221, postgres tpcds [local] con150 cmd16 EXPLAIN
postgres 22294 20939 0 03:03 ? 00:00:00 postgres: 9210, postgres tpcds 172.17.0.50(60732) con150 seg0 cmd17 slice1 MPPEXEC SELECT
postgres 22295 20950 0 03:03 ? 00:00:00 postgres: 9211, postgres tpcds 172.17.0.50(36177) con150 seg1 cmd17 slice1 MPPEXEC SELECT
postgres 22306 20939 5 03:03 ? 00:00:04 postgres: 9210, postgres tpcds 172.17.0.50(60742) con150 seg0 idle
postgres 22307 20950 5 03:03 ? 00:00:04 postgres: 9211, postgres tpcds 172.17.0.50(36187) con150 seg1 idle
postgres 22310 20939 11 03:03 ? 00:00:10 postgres: 9210, postgres tpcds 172.17.0.50(60745) con150 seg0 idle
postgres 22311 20950 12 03:03 ? 00:00:11 postgres: 9211, postgres tpcds 172.17.0.50(36190) con150 seg1 idle
postgres 22314 20939 5 03:03 ? 00:00:04 postgres: 9210, postgres tpcds 172.17.0.50(60748) con150 seg0 idle
postgres 22315 20950 5 03:03 ? 00:00:04 postgres: 9211, postgres tpcds 172.17.0.50(36193) con150 seg1 idle
postgres 22318 20939 1 03:03 ? 00:00:01 postgres: 9210, postgres tpcds 172.17.0.50(60750) con150 seg0 idle
postgres 22319 20950 2 03:03 ? 00:00:01 postgres: 9211, postgres tpcds 172.17.0.50(36195) con150 seg1 idle
postgres 22322 20912 0 03:03 ? 00:00:00 postgres: 9221, postgres tpcds [local] con150 seg-1 idle
postgres 22324 20939 0 03:03 ? 00:00:00 postgres: 9210, postgres tpcds 172.17.0.50(60754) con150 seg0 idle
postgres 22325 20950 0 03:03 ? 00:00:00 postgres: 9211, postgres tpcds 172.17.0.50(36199) con150 seg1 idle
postgres 22348 20939 0 03:05 ? 00:00:00 postgres: 9210, postgres tpcds 172.17.0.50(45936) con150 seg0 idle
postgres 22349 20950 0 03:05 ? 00:00:00 postgres: 9211, postgres tpcds 172.17.0.50(49614) con150 seg1 idle
postgres 22352 20939 4 03:05 ? 00:00:00 postgres: 9210, postgres tpcds 172.17.0.50(45939) con150 seg0 idle
postgres 22353 20950 4 03:05 ? 00:00:00 postgres: 9211, postgres tpcds 172.17.0.50(49617) con150 seg1 idle
```
According to my debugging, the stack of slice 1 processes looks like:
```
#0 0x00007fde606f94f3 in epoll_wait () from /lib64/libc.so.6
#1 0x0000000000d2eec1 in WaitEventSetWaitBlock (set=0x87d8fe0, cur_timeout=-1, occurred_events=0x7ffce695fe00, nevents=1) at latch.c:1081
#2 0x0000000000d2ed9a in WaitEventSetWait (set=0x87d8fe0, timeout=-1, occurred_events=0x7ffce695fe00, nevents=1, wait_event_info=0) at latch.c:1033
#3 0x0000000000d5987d in ConditionVariableSleep (cv=0x7fde540890b0, wait_event_info=0) at condition_variable.c:157
#4 0x0000000000b30a61 in shareinput_writer_waitdone (ref=0x87da950, nconsumers=1) at nodeShareInputScan.c:994
#5 0x0000000000b2fe89 in ExecEndShareInputScan (node=0x88c2ec0) at nodeShareInputScan.c:522
#6 0x0000000000ad63e8 in ExecEndNode (node=0x88c2ec0) at execProcnode.c:888
#7 0x0000000000b3237b in ExecEndSequence (node=0x88c2d80) at nodeSequence.c:132
#8 0x0000000000ad623f in ExecEndNode (node=0x88c2d80) at execProcnode.c:779
#9 0x0000000000b1772e in ExecEndSort (node=0x88c2658) at nodeSort.c:365
```
That is to say, the producer is waiting for consumers to wake it up, while the consumers didn't. According to further debugging, I found a **squelch** is triggered on the *Gather Motion* node upstream of three ShareInputScan consumer nodes. In the squelch logic of ShareInputScan, the consumer will notify producer only if `ndone == nsharers`:
```c
local_state->ndone++;
if (local_state->ndone == local_state->nsharers)
{
shareinput_reader_notifydone(node->ref, sisc->nconsumers);
local_state->closed = true;
}
```
While `ndone` will be accumulated one by one consumer, `nsharers` is initialized in ExecInitNode. However, GUC `execute_pruned_plan` affects the root node where the Executor starts to call `ExecInitNode`:
- `execute_pruned_plan` set to true: the initialization will start at the root node of slice 9, `nsharers` will be 3
- `execute_pruned_plan` set to false: the initialization will start at the root node of the whole plan tree, `nsharers` will be 4, then `ndone == nsharers` will never establish, because we only have three consumers, `ndone` will be 3 at most
According to my understanding, the algorithm should work well no matter this GUC is set to true or false. So I add some conditions in the process of initialization of `nsharers`: to accumulate `nsharers` only when initializing consumer nodes of current slice. Then this algorithm should be working fine.
beeender
pushed a commit
that referenced
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Dec 15, 2022
We used to rename index-backed constraints in the EXCHANGE PARTITION command in 6X. Now we don't. We've decided to keep that behavior in 7X after looking into the opposing arguments: Argument #1. It might cause problem during upgrade. - Firstly, we won't be using legacy syntax in the dump scripts so we just need to worry about the existing tables produced by EXCHANGE PARTITION. I.e. whether or not they can be restored correctly. - For upgrading from 6X->7X, since those tables already have matched constraint and index names with the table names, we should be OK. - For upgrading 7X->onward, since we implement EXCHANGE PARTIITON simply as a combination of upstream-syntax commands (see AtExecGPExchangePartition()), pg_upgrade should be able to handle them. We've verified that manually and the automated test should cover that too. In fact, this gives another point that we shouldn't do our own hacky things as part of EXCHANGE PARTITION which might confuse pg_upgrade. Argument #2. It might surprise the users and their existing workloads. - The indexed constraint names are all implicitly generated and shouldn't be directly used in most cases. - They are not the only thing that will appear changed. E.g. the normal indexes (e.g. B-tree ones) will be too. So the decision to change one should be made with changing all of them. More details see: https://docs.google.com/document/d/1enJdKYxkk5WFRV1WoqIgLgRxCGxOqI2nglJVE_Wglec
beeender
pushed a commit
that referenced
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Nov 2, 2023
gpdb_get_master_data_dir should set master_data_dir variable with non-NULL pointer. However, there is codepath in this function that leads to NULL result. We need to check this case and finish gpmon process with error if any trouble. This case is really reproduced in our production (gdb) bt #0 __strlen_avx2 () at ../sysdeps/x86_64/multiarch/strlen-avx2.S:65 #1 0x00007f18fc1de9ce in __GI___strdup (s=0x0) at strdup.c:41 #2 0x000055ff3885813d in getconfig () at gpmmon.c:1679 #3 main (argc=<optimized out>, argv=<optimized out>) at gpmmon.c:1358 (gdb) Quit
beeender
pushed a commit
that referenced
this pull request
Nov 6, 2023
…586) My previous commit 8915cd0 caused coredump in some pipeline jobs. Example stack: ``` Core was generated by `postgres: 7000, ic proxy process Program terminated with signal SIGSEGV, Segmentation fault. #0 0x0000000000b46ec3 in pg_atomic_read_u32_impl (ptr=0x7f05a8c51104) at ../../../../src/include/port/atomics/generic.h:48 (gdb) bt #0 0x0000000000b46ec3 in pg_atomic_read_u32_impl (ptr=0x7f05a8c51104) at ../../../../src/include/port/atomics/generic.h:48 #1 pg_atomic_read_u32 (ptr=0x7f05a8c51104) at ../../../../src/include/port/atomics.h:247 #2 LWLockAttemptLock (mode=LW_EXCLUSIVE, lock=0x7f05a8c51100) at lwlock.c:751 #3 LWLockAcquire (lock=0x7f05a8c51100, mode=mode@entry=LW_EXCLUSIVE) at lwlock.c:1188 #4 0x0000000000b32fff in ShmemInitStruct (name=name@entry=0x130e160 "", size=size@entry=4, foundPtr=foundPtr@entry=0x7ffcf94513bf) at shmem.c:412 #5 0x0000000000d6d18e in ic_proxy_server_main () at ic_proxy_main.c:545 #6 0x0000000000d6c219 in ICProxyMain (main_arg=<optimized out>) at ic_proxy_bgworker.c:36 #7 0x0000000000aa9caa in StartBackgroundWorker () at bgworker.c:955 #8 0x0000000000ab9407 in do_start_bgworker (rw=<optimized out>) at postmaster.c:6450 #9 maybe_start_bgworkers () at postmaster.c:6706 #10 0x0000000000abbc59 in ServerLoop () at postmaster.c:2095 #11 0x0000000000abd777 in PostmasterMain (argc=argc@entry=5, argv=argv@entry=0x36e3650) at postmaster.c:1633 #12 0x00000000006e4764 in main (argc=5, argv=0x36e3650) at main.c:240 (gdb) p *ptr Cannot access memory at address 0x7f05a8c51104 ``` The root cause is I forgot to init SHM structure at CreateSharedMemoryAndSemaphores(). Fix it in this commit.
beeender
added a commit
that referenced
this pull request
Jan 19, 2024
## Problem
An error occurs in python lib when a plpython function is executed.
After our analysis, in the user's cluster, a plpython UDF
was running with the unstable network, and got a timeout error:
`failed to acquire resources on one or more segments`.
Then a plpython UDF was run in the same session, and the UDF
failed with GC error.
Here is the core dump:
```
2023-11-24 10:15:18.945507 CST,,,p2705198,th2081832064,,,,0,,,seg-1,,,,,"LOG","00000","3rd party error log:
#0 0x7f7c68b6d55b in frame_dealloc /home/cc/repo/cpython/Objects/frameobject.c:509:5
#1 0x7f7c68b5109d in gen_send_ex /home/cc/repo/cpython/Objects/genobject.c:108:9
#2 0x7f7c68af9ddd in PyIter_Next /home/cc/repo/cpython/Objects/abstract.c:3118:14
#3 0x7f7c78caa5c0 in PLy_exec_function /home/cc/repo/gpdb6/src/pl/plpython/plpy_exec.c:134:11
#4 0x7f7c78cb5ffb in plpython_call_handler /home/cc/repo/gpdb6/src/pl/plpython/plpy_main.c:387:13
#5 0x562f5e008bb5 in ExecMakeTableFunctionResult /home/cc/repo/gpdb6/src/backend/executor/execQual.c:2395:13
#6 0x562f5e0dddec in FunctionNext_guts /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:142:5
#7 0x562f5e0da094 in FunctionNext /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:350:11
#8 0x562f5e03d4b0 in ExecScanFetch /home/cc/repo/gpdb6/src/backend/executor/execScan.c:84:9
#9 0x562f5e03cd8f in ExecScan /home/cc/repo/gpdb6/src/backend/executor/execScan.c:154:10
#10 0x562f5e0da072 in ExecFunctionScan /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:380:9
#11 0x562f5e001a1c in ExecProcNode /home/cc/repo/gpdb6/src/backend/executor/execProcnode.c:1071:13
#12 0x562f5dfe6377 in ExecutePlan /home/cc/repo/gpdb6/src/backend/executor/execMain.c:3202:10
#13 0x562f5dfe5bf4 in standard_ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:1171:5
#14 0x562f5dfe4877 in ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:992:4
#15 0x562f5e857e69 in PortalRunSelect /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1164:4
#16 0x562f5e856d3f in PortalRun /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1005:18
#17 0x562f5e84607a in exec_simple_query /home/cc/repo/gpdb6/src/backend/tcop/postgres.c:1848:10
```
## Reproduce
We can use a simple procedure to reproduce the above problem:
- set timeout GUC: `gpconfig -c gp_segment_connect_timeout -v 5` and `gpstop -ari`
- prepare function:
```
CREATE EXTENSION plpythonu;
CREATE OR REPLACE FUNCTION test_func() RETURNS SETOF int AS
$$
plpy.execute("select pg_backend_pid()")
for i in range(0, 5):
yield (i)
$$ LANGUAGE plpythonu;
```
- exit from the current psql session.
- stop the postmaster of segment: `gdb -p "the pid of segment postmaster"`
- enter a psql session.
- call `SELECT test_func();` and get error
```
gpadmin=# select test_func();
ERROR: function "test_func" error fetching next item from iterator (plpy_elog.c:121)
DETAIL: Exception: failed to acquire resources on one or more segments
CONTEXT: Traceback (most recent call last):
PL/Python function "test_func"
```
- quit gdb and make postmaster runnable.
- call `SELECT test_func();` again and get panic
```
gpadmin=# SELECT test_func();
server closed the connection unexpectedly
This probably means the server terminated abnormally
before or while processing the request.
The connection to the server was lost. Attempting reset: Failed.
!>
```
## Analysis
- There is an SPI call in test_func(): `plpy.execute()`.
- Then coordinator will start a subtransaction by PLy_spi_subtransaction_begin();
- Meanwhile, if the segment cannot receive the instruction from the coordinator,
the subtransaction beginning procedure return fails.
- BUT! The Python processor does not know whether an error happened and
does not clean its environment.
- Then the next plpython UDF in the same session will fail due to the wrong
Python environment.
## Solution
- Use try-catch to catch the exception caused by PLy_spi_subtransaction_begin()
- set the python error indicator by PLy_spi_exception_set()
backport from #16856
Co-authored-by: Chen Mulong <chenmulong@gmail.com>
beeender
pushed a commit
that referenced
this pull request
Jan 19, 2024
An error occurs in python lib when a plpython function is executed.
After our analysis, in the user's cluster, a plpython UDF
was running with the unstable network, and got a timeout error:
`failed to acquire resources on one or more segments`.
Then a plpython UDF was run in the same session, and the UDF
failed with GC error.
Here is the core dump:
```
2023-11-24 10:15:18.945507 CST,,,p2705198,th2081832064,,,,0,,,seg-1,,,,,"LOG","00000","3rd party error log:
#0 0x7f7c68b6d55b in frame_dealloc /home/cc/repo/cpython/Objects/frameobject.c:509:5
#1 0x7f7c68b5109d in gen_send_ex /home/cc/repo/cpython/Objects/genobject.c:108:9
#2 0x7f7c68af9ddd in PyIter_Next /home/cc/repo/cpython/Objects/abstract.c:3118:14
#3 0x7f7c78caa5c0 in PLy_exec_function /home/cc/repo/gpdb6/src/pl/plpython/plpy_exec.c:134:11
#4 0x7f7c78cb5ffb in plpython_call_handler /home/cc/repo/gpdb6/src/pl/plpython/plpy_main.c:387:13
#5 0x562f5e008bb5 in ExecMakeTableFunctionResult /home/cc/repo/gpdb6/src/backend/executor/execQual.c:2395:13
#6 0x562f5e0dddec in FunctionNext_guts /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:142:5
#7 0x562f5e0da094 in FunctionNext /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:350:11
#8 0x562f5e03d4b0 in ExecScanFetch /home/cc/repo/gpdb6/src/backend/executor/execScan.c:84:9
#9 0x562f5e03cd8f in ExecScan /home/cc/repo/gpdb6/src/backend/executor/execScan.c:154:10
#10 0x562f5e0da072 in ExecFunctionScan /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:380:9
#11 0x562f5e001a1c in ExecProcNode /home/cc/repo/gpdb6/src/backend/executor/execProcnode.c:1071:13
#12 0x562f5dfe6377 in ExecutePlan /home/cc/repo/gpdb6/src/backend/executor/execMain.c:3202:10
#13 0x562f5dfe5bf4 in standard_ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:1171:5
#14 0x562f5dfe4877 in ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:992:4
#15 0x562f5e857e69 in PortalRunSelect /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1164:4
#16 0x562f5e856d3f in PortalRun /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1005:18
#17 0x562f5e84607a in exec_simple_query /home/cc/repo/gpdb6/src/backend/tcop/postgres.c:1848:10
```
We can use a simple procedure to reproduce the above problem:
- set timeout GUC: `gpconfig -c gp_segment_connect_timeout -v 5` and `gpstop -ari`
- prepare function:
```
CREATE EXTENSION plpythonu;
CREATE OR REPLACE FUNCTION test_func() RETURNS SETOF int AS
$$
plpy.execute("select pg_backend_pid()")
for i in range(0, 5):
yield (i)
$$ LANGUAGE plpythonu;
```
- exit from the current psql session.
- stop the postmaster of segment: `gdb -p "the pid of segment postmaster"`
- enter a psql session.
- call `SELECT test_func();` and get error
```
gpadmin=# select test_func();
ERROR: function "test_func" error fetching next item from iterator (plpy_elog.c:121)
DETAIL: Exception: failed to acquire resources on one or more segments
CONTEXT: Traceback (most recent call last):
PL/Python function "test_func"
```
- quit gdb and make postmaster runnable.
- call `SELECT test_func();` again and get panic
```
gpadmin=# SELECT test_func();
server closed the connection unexpectedly
This probably means the server terminated abnormally
before or while processing the request.
The connection to the server was lost. Attempting reset: Failed.
!>
```
- There is an SPI call in test_func(): `plpy.execute()`.
- Then coordinator will start a subtransaction by PLy_spi_subtransaction_begin();
- Meanwhile, if the segment cannot receive the instruction from the coordinator,
the subtransaction beginning procedure return fails.
- BUT! The Python processor does not know whether an error happened and
does not clean its environment.
- Then the next plpython UDF in the same session will fail due to the wrong
Python environment.
- Use try-catch to catch the exception caused by PLy_spi_subtransaction_begin()
- set the python error indicator by PLy_spi_exception_set()
backport from #16856
Co-authored-by: Chen Mulong <chenmulong@gmail.com>
(cherry picked from commit 45d6ba8)
beeender
added a commit
that referenced
this pull request
Mar 7, 2024
## Problem
An error occurs in python lib when a plpython function is executed.
After our analysis, in the user's cluster, a plpython UDF
was running with the unstable network, and got a timeout error:
`failed to acquire resources on one or more segments`.
Then a plpython UDF was run in the same session, and the UDF
failed with GC error.
Here is the core dump:
```
2023-11-24 10:15:18.945507 CST,,,p2705198,th2081832064,,,,0,,,seg-1,,,,,"LOG","00000","3rd party error log:
#0 0x7f7c68b6d55b in frame_dealloc /home/cc/repo/cpython/Objects/frameobject.c:509:5
#1 0x7f7c68b5109d in gen_send_ex /home/cc/repo/cpython/Objects/genobject.c:108:9
#2 0x7f7c68af9ddd in PyIter_Next /home/cc/repo/cpython/Objects/abstract.c:3118:14
#3 0x7f7c78caa5c0 in PLy_exec_function /home/cc/repo/gpdb6/src/pl/plpython/plpy_exec.c:134:11
#4 0x7f7c78cb5ffb in plpython_call_handler /home/cc/repo/gpdb6/src/pl/plpython/plpy_main.c:387:13
#5 0x562f5e008bb5 in ExecMakeTableFunctionResult /home/cc/repo/gpdb6/src/backend/executor/execQual.c:2395:13
#6 0x562f5e0dddec in FunctionNext_guts /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:142:5
#7 0x562f5e0da094 in FunctionNext /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:350:11
#8 0x562f5e03d4b0 in ExecScanFetch /home/cc/repo/gpdb6/src/backend/executor/execScan.c:84:9
#9 0x562f5e03cd8f in ExecScan /home/cc/repo/gpdb6/src/backend/executor/execScan.c:154:10
#10 0x562f5e0da072 in ExecFunctionScan /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:380:9
#11 0x562f5e001a1c in ExecProcNode /home/cc/repo/gpdb6/src/backend/executor/execProcnode.c:1071:13
#12 0x562f5dfe6377 in ExecutePlan /home/cc/repo/gpdb6/src/backend/executor/execMain.c:3202:10
#13 0x562f5dfe5bf4 in standard_ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:1171:5
#14 0x562f5dfe4877 in ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:992:4
#15 0x562f5e857e69 in PortalRunSelect /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1164:4
#16 0x562f5e856d3f in PortalRun /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1005:18
#17 0x562f5e84607a in exec_simple_query /home/cc/repo/gpdb6/src/backend/tcop/postgres.c:1848:10
```
## Reproduce
We can use a simple procedure to reproduce the above problem:
- set timeout GUC: `gpconfig -c gp_segment_connect_timeout -v 5` and `gpstop -ari`
- prepare function:
```
CREATE EXTENSION plpythonu;
CREATE OR REPLACE FUNCTION test_func() RETURNS SETOF int AS
$$
plpy.execute("select pg_backend_pid()")
for i in range(0, 5):
yield (i)
$$ LANGUAGE plpythonu;
```
- exit from the current psql session.
- stop the postmaster of segment: `gdb -p "the pid of segment postmaster"`
- enter a psql session.
- call `SELECT test_func();` and get error
```
gpadmin=# select test_func();
ERROR: function "test_func" error fetching next item from iterator (plpy_elog.c:121)
DETAIL: Exception: failed to acquire resources on one or more segments
CONTEXT: Traceback (most recent call last):
PL/Python function "test_func"
```
- quit gdb and make postmaster runnable.
- call `SELECT test_func();` again and get panic
```
gpadmin=# SELECT test_func();
server closed the connection unexpectedly
This probably means the server terminated abnormally
before or while processing the request.
The connection to the server was lost. Attempting reset: Failed.
!>
```
## Analysis
- There is an SPI call in test_func(): `plpy.execute()`.
- Then coordinator will start a subtransaction by PLy_spi_subtransaction_begin();
- Meanwhile, if the segment cannot receive the instruction from the coordinator,
the subtransaction beginning procedure return fails.
- BUT! The Python processor does not know whether an error happened and
does not clean its environment.
- Then the next plpython UDF in the same session will fail due to the wrong
Python environment.
## Solution
- Use try-catch to catch the exception caused by PLy_spi_subtransaction_begin()
- set the python error indicator by PLy_spi_exception_set()
Co-authored-by: Chen Mulong <chenmulong@gmail.com>
beeender
added a commit
that referenced
this pull request
Apr 1, 2024
An error occurs in python lib when a plpython function is executed.
After our analysis, in the user's cluster, a plpython UDF
was running with the unstable network, and got a timeout error:
`failed to acquire resources on one or more segments`.
Then a plpython UDF was run in the same session, and the UDF
failed with GC error.
Here is the core dump:
```
2023-11-24 10:15:18.945507 CST,,,p2705198,th2081832064,,,,0,,,seg-1,,,,,"LOG","00000","3rd party error log:
#0 0x7f7c68b6d55b in frame_dealloc /home/cc/repo/cpython/Objects/frameobject.c:509:5
#1 0x7f7c68b5109d in gen_send_ex /home/cc/repo/cpython/Objects/genobject.c:108:9
#2 0x7f7c68af9ddd in PyIter_Next /home/cc/repo/cpython/Objects/abstract.c:3118:14
#3 0x7f7c78caa5c0 in PLy_exec_function /home/cc/repo/gpdb6/src/pl/plpython/plpy_exec.c:134:11
#4 0x7f7c78cb5ffb in plpython_call_handler /home/cc/repo/gpdb6/src/pl/plpython/plpy_main.c:387:13
#5 0x562f5e008bb5 in ExecMakeTableFunctionResult /home/cc/repo/gpdb6/src/backend/executor/execQual.c:2395:13
#6 0x562f5e0dddec in FunctionNext_guts /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:142:5
#7 0x562f5e0da094 in FunctionNext /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:350:11
#8 0x562f5e03d4b0 in ExecScanFetch /home/cc/repo/gpdb6/src/backend/executor/execScan.c:84:9
#9 0x562f5e03cd8f in ExecScan /home/cc/repo/gpdb6/src/backend/executor/execScan.c:154:10
#10 0x562f5e0da072 in ExecFunctionScan /home/cc/repo/gpdb6/src/backend/executor/nodeFunctionscan.c:380:9
#11 0x562f5e001a1c in ExecProcNode /home/cc/repo/gpdb6/src/backend/executor/execProcnode.c:1071:13
#12 0x562f5dfe6377 in ExecutePlan /home/cc/repo/gpdb6/src/backend/executor/execMain.c:3202:10
#13 0x562f5dfe5bf4 in standard_ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:1171:5
#14 0x562f5dfe4877 in ExecutorRun /home/cc/repo/gpdb6/src/backend/executor/execMain.c:992:4
#15 0x562f5e857e69 in PortalRunSelect /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1164:4
#16 0x562f5e856d3f in PortalRun /home/cc/repo/gpdb6/src/backend/tcop/pquery.c:1005:18
#17 0x562f5e84607a in exec_simple_query /home/cc/repo/gpdb6/src/backend/tcop/postgres.c:1848:10
```
We can use a simple procedure to reproduce the above problem:
- set timeout GUC: `gpconfig -c gp_segment_connect_timeout -v 5` and `gpstop -ari`
- prepare function:
```
CREATE EXTENSION plpythonu;
CREATE OR REPLACE FUNCTION test_func() RETURNS SETOF int AS
$$
plpy.execute("select pg_backend_pid()")
for i in range(0, 5):
yield (i)
$$ LANGUAGE plpythonu;
```
- exit from the current psql session.
- stop the postmaster of segment: `gdb -p "the pid of segment postmaster"`
- enter a psql session.
- call `SELECT test_func();` and get error
```
gpadmin=# select test_func();
ERROR: function "test_func" error fetching next item from iterator (plpy_elog.c:121)
DETAIL: Exception: failed to acquire resources on one or more segments
CONTEXT: Traceback (most recent call last):
PL/Python function "test_func"
```
- quit gdb and make postmaster runnable.
- call `SELECT test_func();` again and get panic
```
gpadmin=# SELECT test_func();
server closed the connection unexpectedly
This probably means the server terminated abnormally
before or while processing the request.
The connection to the server was lost. Attempting reset: Failed.
!>
```
- There is an SPI call in test_func(): `plpy.execute()`.
- Then coordinator will start a subtransaction by PLy_spi_subtransaction_begin();
- Meanwhile, if the segment cannot receive the instruction from the coordinator,
the subtransaction beginning procedure return fails.
- BUT! The Python processor does not know whether an error happened and
does not clean its environment.
- Then the next plpython UDF in the same session will fail due to the wrong
Python environment.
- Use try-catch to catch the exception caused by PLy_spi_subtransaction_begin()
- set the python error indicator by PLy_spi_exception_set()
backport from #16856
Co-authored-by: Chen Mulong <chenmulong@gmail.com>
(cherry picked from commit 45d6ba8)
Co-authored-by: Zhang Hao <hzhang2@vmware.com>
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make installcheckadd plpython3 path and guc warning