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Support SHOW ALL VERBOSE to show settings description #7735

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Oct 7, 2023
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15 changes: 10 additions & 5 deletions datafusion/core/src/catalog/information_schema.rs
Original file line number Diff line number Diff line change
Expand Up @@ -626,7 +626,8 @@ impl InformationSchemaDfSettings {
fn new(config: InformationSchemaConfig) -> Self {
let schema = Arc::new(Schema::new(vec![
Field::new("name", DataType::Utf8, false),
Field::new("setting", DataType::Utf8, true),
Field::new("value", DataType::Utf8, true),
Field::new("description", DataType::Utf8, true),
]));

Self { schema, config }
Expand All @@ -635,7 +636,8 @@ impl InformationSchemaDfSettings {
fn builder(&self) -> InformationSchemaDfSettingsBuilder {
InformationSchemaDfSettingsBuilder {
names: StringBuilder::new(),
settings: StringBuilder::new(),
values: StringBuilder::new(),
descriptions: StringBuilder::new(),
schema: self.schema.clone(),
}
}
Expand Down Expand Up @@ -664,21 +666,24 @@ impl PartitionStream for InformationSchemaDfSettings {
struct InformationSchemaDfSettingsBuilder {
schema: SchemaRef,
names: StringBuilder,
settings: StringBuilder,
values: StringBuilder,
descriptions: StringBuilder,
}

impl InformationSchemaDfSettingsBuilder {
fn add_setting(&mut self, entry: ConfigEntry) {
self.names.append_value(entry.key);
self.settings.append_option(entry.value);
self.values.append_option(entry.value);
self.descriptions.append_value(entry.description);
}

fn finish(&mut self) -> RecordBatch {
RecordBatch::try_new(
self.schema.clone(),
vec![
Arc::new(self.names.finish()),
Arc::new(self.settings.finish()),
Arc::new(self.values.finish()),
Arc::new(self.descriptions.finish()),
],
)
.unwrap()
Expand Down
12 changes: 5 additions & 7 deletions datafusion/sql/src/statement.rs
Original file line number Diff line number Diff line change
Expand Up @@ -766,19 +766,17 @@ impl<'a, S: ContextProvider> SqlToRel<'a, S> {
}

let variable_lower = variable.to_lowercase();
let base_query =
"SELECT name, value, description FROM information_schema.df_settings";

let query = if variable_lower == "all" {
// Add an ORDER BY so the output comes out in a consistent order
String::from(
"SELECT name, setting FROM information_schema.df_settings ORDER BY name",
)
format!("{base_query} ORDER BY name")
} else if variable_lower == "timezone" || variable_lower == "time.zone" {
// we could introduce alias in OptionDefinition if this string matching thing grows
String::from("SELECT name, setting FROM information_schema.df_settings WHERE name = 'datafusion.execution.time_zone'")
format!("{base_query} WHERE name = 'datafusion.execution.time_zone'")
} else {
format!(
"SELECT name, setting FROM information_schema.df_settings WHERE name = '{variable}'"
)
format!("{base_query} WHERE name = '{variable}'")
};

let mut rewrite = DFParser::parse_sql(&query)?;
Expand Down
138 changes: 69 additions & 69 deletions datafusion/sqllogictest/test_files/information_schema.slt
Original file line number Diff line number Diff line change
Expand Up @@ -136,91 +136,91 @@ statement ok
SET datafusion.execution.parquet.created_by=datafusion

# show all variables
query TT rowsort
query TTT rowsort
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🥇

SHOW ALL
----
datafusion.catalog.create_default_catalog_and_schema true
datafusion.catalog.default_catalog datafusion
datafusion.catalog.default_schema public
datafusion.catalog.format NULL
datafusion.catalog.has_header false
datafusion.catalog.information_schema true
datafusion.catalog.location NULL
datafusion.execution.aggregate.scalar_update_factor 10
datafusion.execution.batch_size 8192
datafusion.execution.coalesce_batches true
datafusion.execution.collect_statistics false
datafusion.execution.meta_fetch_concurrency 32
datafusion.execution.parquet.allow_single_file_parallelism false
datafusion.execution.parquet.bloom_filter_enabled false
datafusion.execution.parquet.bloom_filter_fpp NULL
datafusion.execution.parquet.bloom_filter_ndv NULL
datafusion.execution.parquet.column_index_truncate_length NULL
datafusion.execution.parquet.compression zstd(3)
datafusion.execution.parquet.created_by datafusion
datafusion.execution.parquet.data_page_row_count_limit 18446744073709551615
datafusion.execution.parquet.data_pagesize_limit 1048576
datafusion.execution.parquet.dictionary_enabled NULL
datafusion.execution.parquet.dictionary_page_size_limit 1048576
datafusion.execution.parquet.enable_page_index true
datafusion.execution.parquet.encoding NULL
datafusion.execution.parquet.max_row_group_size 1048576
datafusion.execution.parquet.max_statistics_size NULL
datafusion.execution.parquet.metadata_size_hint NULL
datafusion.execution.parquet.pruning true
datafusion.execution.parquet.pushdown_filters false
datafusion.execution.parquet.reorder_filters false
datafusion.execution.parquet.skip_metadata true
datafusion.execution.parquet.statistics_enabled NULL
datafusion.execution.parquet.write_batch_size 1024
datafusion.execution.parquet.writer_version 1.0
datafusion.execution.planning_concurrency 13
datafusion.execution.sort_in_place_threshold_bytes 1048576
datafusion.execution.sort_spill_reservation_bytes 10485760
datafusion.execution.target_partitions 7
datafusion.execution.time_zone +00:00
datafusion.explain.logical_plan_only false
datafusion.explain.physical_plan_only false
datafusion.explain.show_statistics false
datafusion.optimizer.allow_symmetric_joins_without_pruning true
datafusion.optimizer.bounded_order_preserving_variants false
datafusion.optimizer.enable_round_robin_repartition true
datafusion.optimizer.enable_topk_aggregation true
datafusion.optimizer.filter_null_join_keys false
datafusion.optimizer.hash_join_single_partition_threshold 1048576
datafusion.optimizer.max_passes 3
datafusion.optimizer.prefer_hash_join true
datafusion.optimizer.repartition_aggregations true
datafusion.optimizer.repartition_file_min_size 10485760
datafusion.optimizer.repartition_file_scans true
datafusion.optimizer.repartition_joins true
datafusion.optimizer.repartition_sorts true
datafusion.optimizer.repartition_windows true
datafusion.optimizer.skip_failed_rules false
datafusion.optimizer.top_down_join_key_reordering true
datafusion.sql_parser.dialect generic
datafusion.sql_parser.enable_ident_normalization true
datafusion.sql_parser.parse_float_as_decimal false
datafusion.catalog.create_default_catalog_and_schema true Whether the default catalog and schema should be created automatically.
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datafusion.catalog.default_catalog datafusion The default catalog name - this impacts what SQL queries use if not specified
datafusion.catalog.default_schema public The default schema name - this impacts what SQL queries use if not specified
datafusion.catalog.format NULL Type of `TableProvider` to use when loading `default` schema
datafusion.catalog.has_header false If the file has a header
datafusion.catalog.information_schema true Should DataFusion provide access to `information_schema` virtual tables for displaying schema information
datafusion.catalog.location NULL Location scanned to load tables for `default` schema
datafusion.execution.aggregate.scalar_update_factor 10 Specifies the threshold for using `ScalarValue`s to update accumulators during high-cardinality aggregations for each input batch. The aggregation is considered high-cardinality if the number of affected groups is greater than or equal to `batch_size / scalar_update_factor`. In such cases, `ScalarValue`s are utilized for updating accumulators, rather than the default batch-slice approach. This can lead to performance improvements. By adjusting the `scalar_update_factor`, you can balance the trade-off between more efficient accumulator updates and the number of groups affected.
datafusion.execution.batch_size 8192 Default batch size while creating new batches, it's especially useful for buffer-in-memory batches since creating tiny batches would result in too much metadata memory consumption
datafusion.execution.coalesce_batches true When set to true, record batches will be examined between each operator and small batches will be coalesced into larger batches. This is helpful when there are highly selective filters or joins that could produce tiny output batches. The target batch size is determined by the configuration setting
datafusion.execution.collect_statistics false Should DataFusion collect statistics after listing files
datafusion.execution.meta_fetch_concurrency 32 Number of files to read in parallel when inferring schema and statistics
datafusion.execution.parquet.allow_single_file_parallelism false Controls whether DataFusion will attempt to speed up writing large parquet files by first writing multiple smaller files and then stitching them together into a single large file. This will result in faster write speeds, but higher memory usage. Also currently unsupported are bloom filters and column indexes when single_file_parallelism is enabled.
datafusion.execution.parquet.bloom_filter_enabled false Sets if bloom filter is enabled for any column
datafusion.execution.parquet.bloom_filter_fpp NULL Sets bloom filter false positive probability. If NULL, uses default parquet writer setting
datafusion.execution.parquet.bloom_filter_ndv NULL Sets bloom filter number of distinct values. If NULL, uses default parquet writer setting
datafusion.execution.parquet.column_index_truncate_length NULL Sets column index trucate length
datafusion.execution.parquet.compression zstd(3) Sets default parquet compression codec Valid values are: uncompressed, snappy, gzip(level), lzo, brotli(level), lz4, zstd(level), and lz4_raw. These values are not case sensitive. If NULL, uses default parquet writer setting
datafusion.execution.parquet.created_by datafusion Sets "created by" property
datafusion.execution.parquet.data_page_row_count_limit 18446744073709551615 Sets best effort maximum number of rows in data page
datafusion.execution.parquet.data_pagesize_limit 1048576 Sets best effort maximum size of data page in bytes
datafusion.execution.parquet.dictionary_enabled NULL Sets if dictionary encoding is enabled. If NULL, uses default parquet writer setting
datafusion.execution.parquet.dictionary_page_size_limit 1048576 Sets best effort maximum dictionary page size, in bytes
datafusion.execution.parquet.enable_page_index true If true, reads the Parquet data page level metadata (the Page Index), if present, to reduce the I/O and number of rows decoded.
datafusion.execution.parquet.encoding NULL Sets default encoding for any column Valid values are: plain, plain_dictionary, rle, bit_packed, delta_binary_packed, delta_length_byte_array, delta_byte_array, rle_dictionary, and byte_stream_split. These values are not case sensitive. If NULL, uses default parquet writer setting
datafusion.execution.parquet.max_row_group_size 1048576 Sets maximum number of rows in a row group
datafusion.execution.parquet.max_statistics_size NULL Sets max statistics size for any column. If NULL, uses default parquet writer setting
datafusion.execution.parquet.metadata_size_hint NULL If specified, the parquet reader will try and fetch the last `size_hint` bytes of the parquet file optimistically. If not specified, two reads are required: One read to fetch the 8-byte parquet footer and another to fetch the metadata length encoded in the footer
datafusion.execution.parquet.pruning true If true, the parquet reader attempts to skip entire row groups based on the predicate in the query and the metadata (min/max values) stored in the parquet file
datafusion.execution.parquet.pushdown_filters false If true, filter expressions are be applied during the parquet decoding operation to reduce the number of rows decoded
datafusion.execution.parquet.reorder_filters false If true, filter expressions evaluated during the parquet decoding operation will be reordered heuristically to minimize the cost of evaluation. If false, the filters are applied in the same order as written in the query
datafusion.execution.parquet.skip_metadata true If true, the parquet reader skip the optional embedded metadata that may be in the file Schema. This setting can help avoid schema conflicts when querying multiple parquet files with schemas containing compatible types but different metadata
datafusion.execution.parquet.statistics_enabled NULL Sets if statistics are enabled for any column Valid values are: "none", "chunk", and "page" These values are not case sensitive. If NULL, uses default parquet writer setting
datafusion.execution.parquet.write_batch_size 1024 Sets write_batch_size in bytes
datafusion.execution.parquet.writer_version 1.0 Sets parquet writer version valid values are "1.0" and "2.0"
datafusion.execution.planning_concurrency 13 Fan-out during initial physical planning. This is mostly use to plan `UNION` children in parallel. Defaults to the number of CPU cores on the system
datafusion.execution.sort_in_place_threshold_bytes 1048576 When sorting, below what size should data be concatenated and sorted in a single RecordBatch rather than sorted in batches and merged.
datafusion.execution.sort_spill_reservation_bytes 10485760 Specifies the reserved memory for each spillable sort operation to facilitate an in-memory merge. When a sort operation spills to disk, the in-memory data must be sorted and merged before being written to a file. This setting reserves a specific amount of memory for that in-memory sort/merge process. Note: This setting is irrelevant if the sort operation cannot spill (i.e., if there's no `DiskManager` configured).
datafusion.execution.target_partitions 7 Number of partitions for query execution. Increasing partitions can increase concurrency. Defaults to the number of CPU cores on the system
datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour
datafusion.explain.logical_plan_only false When set to true, the explain statement will only print logical plans
datafusion.explain.physical_plan_only false When set to true, the explain statement will only print physical plans
datafusion.explain.show_statistics false When set to true, the explain statement will print operator statistics for physical plans
datafusion.optimizer.allow_symmetric_joins_without_pruning true Should DataFusion allow symmetric hash joins for unbounded data sources even when its inputs do not have any ordering or filtering If the flag is not enabled, the SymmetricHashJoin operator will be unable to prune its internal buffers, resulting in certain join types - such as Full, Left, LeftAnti, LeftSemi, Right, RightAnti, and RightSemi - being produced only at the end of the execution. This is not typical in stream processing. Additionally, without proper design for long runner execution, all types of joins may encounter out-of-memory errors.
datafusion.optimizer.bounded_order_preserving_variants false When true, DataFusion will opportunistically remove sorts by replacing `RepartitionExec` with `SortPreservingRepartitionExec`, and `CoalescePartitionsExec` with `SortPreservingMergeExec`, even when the query is bounded.
datafusion.optimizer.enable_round_robin_repartition true When set to true, the physical plan optimizer will try to add round robin repartitioning to increase parallelism to leverage more CPU cores
datafusion.optimizer.enable_topk_aggregation true When set to true, the optimizer will attempt to perform limit operations during aggregations, if possible
datafusion.optimizer.filter_null_join_keys false When set to true, the optimizer will insert filters before a join between a nullable and non-nullable column to filter out nulls on the nullable side. This filter can add additional overhead when the file format does not fully support predicate push down.
datafusion.optimizer.hash_join_single_partition_threshold 1048576 The maximum estimated size in bytes for one input side of a HashJoin will be collected into a single partition
datafusion.optimizer.max_passes 3 Number of times that the optimizer will attempt to optimize the plan
datafusion.optimizer.prefer_hash_join true When set to true, the physical plan optimizer will prefer HashJoin over SortMergeJoin. HashJoin can work more efficiently than SortMergeJoin but consumes more memory
datafusion.optimizer.repartition_aggregations true Should DataFusion repartition data using the aggregate keys to execute aggregates in parallel using the provided `target_partitions` level
datafusion.optimizer.repartition_file_min_size 10485760 Minimum total files size in bytes to perform file scan repartitioning.
datafusion.optimizer.repartition_file_scans true When set to `true`, file groups will be repartitioned to achieve maximum parallelism. Currently Parquet and CSV formats are supported. If set to `true`, all files will be repartitioned evenly (i.e., a single large file might be partitioned into smaller chunks) for parallel scanning. If set to `false`, different files will be read in parallel, but repartitioning won't happen within a single file.
datafusion.optimizer.repartition_joins true Should DataFusion repartition data using the join keys to execute joins in parallel using the provided `target_partitions` level
datafusion.optimizer.repartition_sorts true Should DataFusion execute sorts in a per-partition fashion and merge afterwards instead of coalescing first and sorting globally. With this flag is enabled, plans in the form below ```text "SortExec: [a@0 ASC]", " CoalescePartitionsExec", " RepartitionExec: partitioning=RoundRobinBatch(8), input_partitions=1", ``` would turn into the plan below which performs better in multithreaded environments ```text "SortPreservingMergeExec: [a@0 ASC]", " SortExec: [a@0 ASC]", " RepartitionExec: partitioning=RoundRobinBatch(8), input_partitions=1", ```
datafusion.optimizer.repartition_windows true Should DataFusion repartition data using the partitions keys to execute window functions in parallel using the provided `target_partitions` level
datafusion.optimizer.skip_failed_rules false When set to true, the logical plan optimizer will produce warning messages if any optimization rules produce errors and then proceed to the next rule. When set to false, any rules that produce errors will cause the query to fail
datafusion.optimizer.top_down_join_key_reordering true When set to true, the physical plan optimizer will run a top down process to reorder the join keys
datafusion.sql_parser.dialect generic Configure the SQL dialect used by DataFusion's parser; supported values include: Generic, MySQL, PostgreSQL, Hive, SQLite, Snowflake, Redshift, MsSQL, ClickHouse, BigQuery, and Ansi.
datafusion.sql_parser.enable_ident_normalization true When set to true, SQL parser will normalize ident (convert ident to lowercase when not quoted)
datafusion.sql_parser.parse_float_as_decimal false When set to true, SQL parser will parse float as decimal type

# show_variable_in_config_options
query TT
query TTT
SHOW datafusion.execution.batch_size
----
datafusion.execution.batch_size 8192
datafusion.execution.batch_size 8192 Default batch size while creating new batches, it's especially useful for buffer-in-memory batches since creating tiny batches would result in too much metadata memory consumption

# show_time_zone_default_utc
# https://github.com/apache/arrow-datafusion/issues/3255
query TT
query TTT
SHOW TIME ZONE
----
datafusion.execution.time_zone +00:00
datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour

# show_timezone_default_utc
# https://github.com/apache/arrow-datafusion/issues/3255
query TT
query TTT
SHOW TIMEZONE
----
datafusion.execution.time_zone +00:00
datafusion.execution.time_zone +00:00 The default time zone Some functions, e.g. `EXTRACT(HOUR from SOME_TIME)`, shift the underlying datetime according to this time zone, and then extract the hour


# information_schema_describe_table
Expand Down
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