This is an automated email from the ASF dual-hosted git repository.
github-bot pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/datafusion.git
The following commit(s) were added to refs/heads/asf-site by this push:
new c14225a3bc Publish built docs triggered by
becc71be04732ca2f62139192dcc76caf6c08fd3
c14225a3bc is described below
commit c14225a3bc888203c4ea3448bf4e74d5392e0f3f
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Wed Nov 12 03:43:21 2025 +0000
Publish built docs triggered by becc71be04732ca2f62139192dcc76caf6c08fd3
---
_sources/user-guide/configs.md.txt | 237 +++++++++++++++++++------------------
searchindex.js | 2 +-
user-guide/configs.html | 108 +++++++++--------
3 files changed, 176 insertions(+), 171 deletions(-)
diff --git a/_sources/user-guide/configs.md.txt
b/_sources/user-guide/configs.md.txt
index 6e5e063a12..c3eda544a1 100644
--- a/_sources/user-guide/configs.md.txt
+++ b/_sources/user-guide/configs.md.txt
@@ -63,124 +63,125 @@ SET datafusion.execution.target_partitions = '1';
The following configuration settings are available:
-| key |
default | description
[...]
-| ----------------------------------------------------------------------- |
------------------------- |
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[...]
-| datafusion.catalog.create_default_catalog_and_schema |
true | Whether the default catalog and schema should be
created automatically.
[...]
-| 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.information_schema |
false | 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.catalog.format |
NULL | Type of `TableProvider` to use when loading
`default` schema
[...]
-| datafusion.catalog.has_header |
true | Default value for `format.has_header` for `CREATE
EXTERNAL TABLE` if not specified explicitly in the statement.
[...]
-| datafusion.catalog.newlines_in_values |
false | Specifies whether newlines in (quoted) CSV values
are supported. This is the default value for `format.newlines_in_values` for
`CREATE EXTERNAL TABLE` if not specified explicitly in the statement. Parsing
newlines in quoted values may be affected by execution behaviour such as
parallel file scanning. Setting this to `true` ensures that newlines in values
are parsed successfully, which [...]
-| 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 |
true | Should DataFusion collect statistics when first
creating a table. Has no effect after the table is created. Applies to the
default `ListingTableProvider` in DataFusion. Defaults to true.
[...]
-| datafusion.execution.target_partitions | 0
| 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 |
NULL | The default time zone Some functions, e.g. `now`
return timestamps in this time zone
[...]
-| datafusion.execution.parquet.enable_page_index |
true | (reading) 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.pruning |
true | (reading) 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.skip_metadata |
true | (reading) 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.metadata_size_hint |
524288 | (reading) 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 Default setting
to 512 KiB, which should be sufficient for most parquet files, it can reduce
one I/O operation per [...]
-| datafusion.execution.parquet.pushdown_filters |
false | (reading) If true, filter expressions are be
applied during the parquet decoding operation to reduce the number of rows
decoded. This optimization is sometimes called "late materialization".
[...]
-| datafusion.execution.parquet.reorder_filters |
false | (reading) 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.schema_force_view_types |
true | (reading) If true, parquet reader will read columns
of `Utf8/Utf8Large` with `Utf8View`, and `Binary/BinaryLarge` with
`BinaryView`.
[...]
-| datafusion.execution.parquet.binary_as_string |
false | (reading) If true, parquet reader will read columns
of `Binary/LargeBinary` with `Utf8`, and `BinaryView` with `Utf8View`. Parquet
files generated by some legacy writers do not correctly set the UTF8 flag for
strings, causing string columns to be loaded as BLOB instead.
[...]
-| datafusion.execution.parquet.coerce_int96 |
NULL | (reading) If true, parquet reader will read columns
of physical type int96 as originating from a different resolution than
nanosecond. This is useful for reading data from systems like Spark which
stores microsecond resolution timestamps in an int96 allowing it to write
values with a larger date range than 64-bit timestamps with nanosecond
resolution. [...]
-| datafusion.execution.parquet.bloom_filter_on_read |
true | (reading) Use any available bloom filters when
reading parquet files
[...]
-| datafusion.execution.parquet.max_predicate_cache_size |
NULL | (reading) The maximum predicate cache size, in
bytes. When `pushdown_filters` is enabled, sets the maximum memory used to
cache the results of predicate evaluation between filter evaluation and output
generation. Decreasing this value will reduce memory usage, but may increase IO
and CPU usage. None means use the default parquet reader setting. 0 means no
caching. [...]
-| datafusion.execution.parquet.data_pagesize_limit |
1048576 | (writing) Sets best effort maximum size of data
page in bytes
[...]
-| datafusion.execution.parquet.write_batch_size |
1024 | (writing) Sets write_batch_size in bytes
[...]
-| datafusion.execution.parquet.writer_version |
1.0 | (writing) Sets parquet writer version valid values
are "1.0" and "2.0"
[...]
-| datafusion.execution.parquet.skip_arrow_metadata |
false | (writing) Skip encoding the embedded arrow metadata
in the KV_meta This is analogous to the
`ArrowWriterOptions::with_skip_arrow_metadata`. Refer to
<https://docs.rs/parquet/53.3.0/parquet/arrow/arrow_writer/struct.ArrowWriterOptions.html#method.with_skip_arrow_metadata>
[...]
-| datafusion.execution.parquet.compression |
zstd(3) | (writing) 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 Note that this default setting is not the same
as the default parquet writer setting.
[...]
-| datafusion.execution.parquet.dictionary_enabled |
true | (writing) Sets if dictionary encoding is enabled.
If NULL, uses default parquet writer setting
[...]
-| datafusion.execution.parquet.dictionary_page_size_limit |
1048576 | (writing) Sets best effort maximum dictionary page
size, in bytes
[...]
-| datafusion.execution.parquet.statistics_enabled |
page | (writing) 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.max_row_group_size |
1048576 | (writing) Target maximum number of rows in each row
group (defaults to 1M rows). Writing larger row groups requires more memory to
write, but can get better compression and be faster to read.
[...]
-| datafusion.execution.parquet.created_by |
datafusion version 51.0.0 | (writing) Sets "created by" property
[...]
-| datafusion.execution.parquet.column_index_truncate_length | 64
| (writing) Sets column index truncate length
[...]
-| datafusion.execution.parquet.statistics_truncate_length | 64
| (writing) Sets statistics truncate length. If NULL,
uses default parquet writer setting
[...]
-| datafusion.execution.parquet.data_page_row_count_limit |
20000 | (writing) Sets best effort maximum number of rows
in data page
[...]
-| datafusion.execution.parquet.encoding |
NULL | (writing) 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.bloom_filter_on_write |
false | (writing) Write bloom filters for all columns when
creating parquet files
[...]
-| datafusion.execution.parquet.bloom_filter_fpp |
NULL | (writing) Sets bloom filter false positive
probability. If NULL, uses default parquet writer setting
[...]
-| datafusion.execution.parquet.bloom_filter_ndv |
NULL | (writing) Sets bloom filter number of distinct
values. If NULL, uses default parquet writer setting
[...]
-| datafusion.execution.parquet.allow_single_file_parallelism |
true | (writing) Controls whether DataFusion will attempt
to speed up writing parquet files by serializing them in parallel. Each column
in each row group in each output file are serialized in parallel leveraging a
maximum possible core count of n_files*n_row_groups*n_columns.
[...]
-| datafusion.execution.parquet.maximum_parallel_row_group_writers | 1
| (writing) By default parallel parquet writer is tuned
for minimum memory usage in a streaming execution plan. You may see a
performance benefit when writing large parquet files by increasing
maximum_parallel_row_group_writers and
maximum_buffered_record_batches_per_stream if your system has idle cores and
can tolerate additional memory usage. Boosting these values is likely
worthwhile [...]
-| datafusion.execution.parquet.maximum_buffered_record_batches_per_stream | 2
| (writing) By default parallel parquet writer is tuned
for minimum memory usage in a streaming execution plan. You may see a
performance benefit when writing large parquet files by increasing
maximum_parallel_row_group_writers and
maximum_buffered_record_batches_per_stream if your system has idle cores and
can tolerate additional memory usage. Boosting these values is likely
worthwhile [...]
-| datafusion.execution.planning_concurrency | 0
| 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.skip_physical_aggregate_schema_check |
false | When set to true, skips verifying that the schema
produced by planning the input of `LogicalPlan::Aggregate` exactly matches the
schema of the input plan. When set to false, if the schema does not match
exactly (including nullability and metadata), a planning error will be raised.
This is used to workaround bugs in the planner that are now caught by the new
schema verification step. [...]
-| datafusion.execution.spill_compression |
uncompressed | Sets the compression codec used when spilling data
to disk. Since datafusion writes spill files using the Arrow IPC Stream format,
only codecs supported by the Arrow IPC Stream Writer are allowed. Valid values
are: uncompressed, lz4_frame, zstd. Note: lz4_frame offers faster
(de)compression, but typically results in larger spill files. In contrast, zstd
achieves higher compression rati [...]
-| 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 [...]
-| 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.max_spill_file_size_bytes |
134217728 | Maximum size in bytes for individual spill files
before rotating to a new file. When operators spill data to disk (e.g.,
RepartitionExec), they write multiple batches to the same file until this size
limit is reached, then rotate to a new file. This reduces syscall overhead
compared to one-file-per-batch while preventing files from growing too large. A
larger value reduces file creatio [...]
-| datafusion.execution.meta_fetch_concurrency | 32
| Number of files to read in parallel when inferring
schema and statistics
[...]
-| datafusion.execution.minimum_parallel_output_files | 4
| Guarantees a minimum level of output files running in
parallel. RecordBatches will be distributed in round robin fashion to each
parallel writer. Each writer is closed and a new file opened once
soft_max_rows_per_output_file is reached.
[...]
-| datafusion.execution.soft_max_rows_per_output_file |
50000000 | Target number of rows in output files when writing
multiple. This is a soft max, so it can be exceeded slightly. There also will
be one file smaller than the limit if the total number of rows written is not
roughly divisible by the soft max
[...]
-| datafusion.execution.max_buffered_batches_per_output_file | 2
| This is the maximum number of RecordBatches buffered
for each output file being worked. Higher values can potentially give faster
write performance at the cost of higher peak memory consumption
[...]
-| datafusion.execution.listing_table_ignore_subdirectory |
true | Should sub directories be ignored when scanning
directories for data files. Defaults to true (ignores subdirectories),
consistent with Hive. Note that this setting does not affect reading
partitioned tables (e.g. `/table/year=2021/month=01/data.parquet`).
[...]
-| datafusion.execution.listing_table_factory_infer_partitions |
true | Should a `ListingTable` created through the
`ListingTableFactory` infer table partitions from Hive compliant directories.
Defaults to true (partition columns are inferred and will be represented in the
table schema).
[...]
-| datafusion.execution.enable_recursive_ctes |
true | Should DataFusion support recursive CTEs
[...]
-| datafusion.execution.split_file_groups_by_statistics |
false | Attempt to eliminate sorts by packing & sorting
files with non-overlapping statistics into the same file groups. Currently
experimental
[...]
-| datafusion.execution.keep_partition_by_columns |
false | Should DataFusion keep the columns used for
partition_by in the output RecordBatches
[...]
-| datafusion.execution.skip_partial_aggregation_probe_ratio_threshold |
0.8 | Aggregation ratio (number of distinct groups /
number of input rows) threshold for skipping partial aggregation. If the value
is greater then partial aggregation will skip aggregation for further input
[...]
-| datafusion.execution.skip_partial_aggregation_probe_rows_threshold |
100000 | Number of input rows partial aggregation partition
should process, before aggregation ratio check and trying to switch to skipping
aggregation mode
[...]
-| datafusion.execution.use_row_number_estimates_to_optimize_partitioning |
false | Should DataFusion use row number estimates at the
input to decide whether increasing parallelism is beneficial or not. By
default, only exact row numbers (not estimates) are used for this decision.
Setting this flag to `true` will likely produce better plans. if the source of
statistics is accurate. We plan to make this the default in the future.
[...]
-| datafusion.execution.enforce_batch_size_in_joins |
false | Should DataFusion enforce batch size in joins or
not. By default, DataFusion will not enforce batch size in joins. Enforcing
batch size in joins can reduce memory usage when joining large tables with a
highly-selective join filter, but is also slightly slower.
[...]
-| datafusion.execution.objectstore_writer_buffer_size |
10485760 | Size (bytes) of data buffer DataFusion uses when
writing output files. This affects the size of the data chunks that are
uploaded to remote object stores (e.g. AWS S3). If very large (>= 100 GiB)
output files are being written, it may be necessary to increase this size to
avoid errors from the remote end point.
[...]
-| datafusion.optimizer.enable_distinct_aggregation_soft_limit |
true | When set to true, the optimizer will push a limit
operation into grouped aggregations which have no aggregate expressions, as a
soft limit, emitting groups once the limit is reached, before all rows in the
group are read.
[...]
-| 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.enable_window_limits |
true | When set to true, the optimizer will attempt to
push limit operations past window functions, if possible
[...]
-| datafusion.optimizer.enable_topk_dynamic_filter_pushdown |
true | When set to true, the optimizer will attempt to
push down TopK dynamic filters into the file scan phase.
[...]
-| datafusion.optimizer.enable_join_dynamic_filter_pushdown |
true | When set to true, the optimizer will attempt to
push down Join dynamic filters into the file scan phase.
[...]
-| datafusion.optimizer.enable_dynamic_filter_pushdown |
true | When set to true attempts to push down dynamic
filters generated by operators (topk & join) into the file scan phase. For
example, for a query such as `SELECT * FROM t ORDER BY timestamp DESC LIMIT
10`, the optimizer will attempt to push down the current top 10 timestamps that
the TopK operator references into the file scans. This means that if we already
have 10 timestamps in the year [...]
-| 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.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_joins |
true | Should DataFusion repartition data using the join
keys to execute joins in parallel using the provided `target_partitions` level
[...]
-| 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 execut [...]
-| datafusion.optimizer.repartition_file_scans |
true | When set to `true`, datasource partitions will be
repartitioned to achieve maximum parallelism. This applies to both in-memory
partitions and FileSource's file groups (1 group is 1 partition). For
FileSources, only Parquet and CSV formats are currently supported. If set to
`true` for a FileSource, all files will be repartitioned evenly (i.e., a single
large file might be partitioned in [...]
-| 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.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 enviro [...]
-| datafusion.optimizer.prefer_existing_sort |
false | When true, DataFusion will opportunistically remove
sorts when the data is already sorted, (i.e. setting `preserve_order` to true
on `RepartitionExec` and using `SortPreservingMergeExec`) When false,
DataFusion will maximize plan parallelism using `RepartitionExec` even if this
requires subsequently resorting data using a `SortExec`.
[...]
-| 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.max_passes | 3
| Number of times that the optimizer will attempt to
optimize the plan
[...]
-| 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.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.enable_piecewise_merge_join |
false | When set to true, piecewise merge join is enabled.
PiecewiseMergeJoin is currently experimental. Physical planner will opt for
PiecewiseMergeJoin when there is only one range filter.
[...]
-| 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.hash_join_single_partition_threshold_rows |
131072 | The maximum estimated size in rows for one input
side of a HashJoin will be collected into a single partition
[...]
-| datafusion.optimizer.default_filter_selectivity | 20
| The default filter selectivity used by Filter
Statistics when an exact selectivity cannot be determined. Valid values are
between 0 (no selectivity) and 100 (all rows are selected).
[...]
-| datafusion.optimizer.prefer_existing_union |
false | When set to true, the optimizer will not attempt to
convert Union to Interleave
[...]
-| datafusion.optimizer.expand_views_at_output |
false | When set to true, if the returned type is a view
type then the output will be coerced to a non-view. Coerces `Utf8View` to
`LargeUtf8`, and `BinaryView` to `LargeBinary`.
[...]
-| 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.explain.show_sizes |
true | When set to true, the explain statement will print
the partition sizes
[...]
-| datafusion.explain.show_schema |
false | When set to true, the explain statement will print
schema information
[...]
-| datafusion.explain.format |
indent | Display format of explain. Default is "indent".
When set to "tree", it will print the plan in a tree-rendered format.
[...]
-| datafusion.explain.tree_maximum_render_width |
240 | (format=tree only) Maximum total width of the
rendered tree. When set to 0, the tree will have no width limit.
[...]
-| datafusion.explain.analyze_level |
dev | Verbosity level for "EXPLAIN ANALYZE". Default is
"dev" "summary" shows common metrics for high-level insights. "dev" provides
deep operator-level introspection for developers.
[...]
-| datafusion.sql_parser.parse_float_as_decimal |
false | When set to true, SQL parser will parse float as
decimal type
[...]
-| 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.enable_options_value_normalization |
false | When set to true, SQL parser will normalize options
value (convert value to lowercase). Note that this option is ignored and will
be removed in the future. All case-insensitive values are normalized
automatically.
[...]
-| 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, Ansi, DuckDB and Databricks.
[...]
-| datafusion.sql_parser.support_varchar_with_length |
true | If true, permit lengths for `VARCHAR` such as
`VARCHAR(20)`, but ignore the length. If false, error if a `VARCHAR` with a
length is specified. The Arrow type system does not have a notion of maximum
string length and thus DataFusion can not enforce such limits.
[...]
-| datafusion.sql_parser.map_string_types_to_utf8view |
true | If true, string types (VARCHAR, CHAR, Text, and
String) are mapped to `Utf8View` during SQL planning. If false, they are mapped
to `Utf8`. Default is true.
[...]
-| datafusion.sql_parser.collect_spans |
false | When set to true, the source locations relative to
the original SQL query (i.e.
[`Span`](https://docs.rs/sqlparser/latest/sqlparser/tokenizer/struct.Span.html))
will be collected and recorded in the logical plan nodes.
[...]
-| datafusion.sql_parser.recursion_limit | 50
| Specifies the recursion depth limit when parsing
complex SQL Queries
[...]
-| datafusion.sql_parser.default_null_ordering |
nulls_max | Specifies the default null ordering for query
results. There are 4 options: - `nulls_max`: Nulls appear last in ascending
order. - `nulls_min`: Nulls appear first in ascending order. - `nulls_first`:
Nulls always be first in any order. - `nulls_last`: Nulls always be last in any
order. By default, `nulls_max` is used to follow Postgres's behavior. postgres
rule: <https://www.postgresql [...]
-| datafusion.format.safe |
true | If set to `true` any formatting errors will be
written to the output instead of being converted into a [`std::fmt::Error`]
[...]
-| datafusion.format.null |
| Format string for nulls
[...]
-| datafusion.format.date_format |
%Y-%m-%d | Date format for date arrays
[...]
-| datafusion.format.datetime_format |
%Y-%m-%dT%H:%M:%S%.f | Format for DateTime arrays
[...]
-| datafusion.format.timestamp_format |
%Y-%m-%dT%H:%M:%S%.f | Timestamp format for timestamp arrays
[...]
-| datafusion.format.timestamp_tz_format |
NULL | Timestamp format for timestamp with timezone
arrays. When `None`, ISO 8601 format is used.
[...]
-| datafusion.format.time_format |
%H:%M:%S%.f | Time format for time arrays
[...]
-| datafusion.format.duration_format |
pretty | Duration format. Can be either `"pretty"` or
`"ISO8601"`
[...]
-| datafusion.format.types_info |
false | Show types in visual representation batches
[...]
+| key |
default | description
[...]
+| ----------------------------------------------------------------------- |
------------------------- |
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
[...]
+| datafusion.catalog.create_default_catalog_and_schema |
true | Whether the default catalog and schema should be
created automatically.
[...]
+| 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.information_schema |
false | 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.catalog.format |
NULL | Type of `TableProvider` to use when loading
`default` schema
[...]
+| datafusion.catalog.has_header |
true | Default value for `format.has_header` for `CREATE
EXTERNAL TABLE` if not specified explicitly in the statement.
[...]
+| datafusion.catalog.newlines_in_values |
false | Specifies whether newlines in (quoted) CSV values
are supported. This is the default value for `format.newlines_in_values` for
`CREATE EXTERNAL TABLE` if not specified explicitly in the statement. Parsing
newlines in quoted values may be affected by execution behaviour such as
parallel file scanning. Setting this to `true` ensures that newlines in values
are parsed successfully, which [...]
+| 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 |
true | Should DataFusion collect statistics when first
creating a table. Has no effect after the table is created. Applies to the
default `ListingTableProvider` in DataFusion. Defaults to true.
[...]
+| datafusion.execution.target_partitions | 0
| 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 |
NULL | The default time zone Some functions, e.g. `now`
return timestamps in this time zone
[...]
+| datafusion.execution.parquet.enable_page_index |
true | (reading) 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.pruning |
true | (reading) 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.skip_metadata |
true | (reading) 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.metadata_size_hint |
524288 | (reading) 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 Default setting
to 512 KiB, which should be sufficient for most parquet files, it can reduce
one I/O operation per [...]
+| datafusion.execution.parquet.pushdown_filters |
false | (reading) If true, filter expressions are be
applied during the parquet decoding operation to reduce the number of rows
decoded. This optimization is sometimes called "late materialization".
[...]
+| datafusion.execution.parquet.reorder_filters |
false | (reading) 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.schema_force_view_types |
true | (reading) If true, parquet reader will read columns
of `Utf8/Utf8Large` with `Utf8View`, and `Binary/BinaryLarge` with
`BinaryView`.
[...]
+| datafusion.execution.parquet.binary_as_string |
false | (reading) If true, parquet reader will read columns
of `Binary/LargeBinary` with `Utf8`, and `BinaryView` with `Utf8View`. Parquet
files generated by some legacy writers do not correctly set the UTF8 flag for
strings, causing string columns to be loaded as BLOB instead.
[...]
+| datafusion.execution.parquet.coerce_int96 |
NULL | (reading) If true, parquet reader will read columns
of physical type int96 as originating from a different resolution than
nanosecond. This is useful for reading data from systems like Spark which
stores microsecond resolution timestamps in an int96 allowing it to write
values with a larger date range than 64-bit timestamps with nanosecond
resolution. [...]
+| datafusion.execution.parquet.bloom_filter_on_read |
true | (reading) Use any available bloom filters when
reading parquet files
[...]
+| datafusion.execution.parquet.max_predicate_cache_size |
NULL | (reading) The maximum predicate cache size, in
bytes. When `pushdown_filters` is enabled, sets the maximum memory used to
cache the results of predicate evaluation between filter evaluation and output
generation. Decreasing this value will reduce memory usage, but may increase IO
and CPU usage. None means use the default parquet reader setting. 0 means no
caching. [...]
+| datafusion.execution.parquet.data_pagesize_limit |
1048576 | (writing) Sets best effort maximum size of data
page in bytes
[...]
+| datafusion.execution.parquet.write_batch_size |
1024 | (writing) Sets write_batch_size in bytes
[...]
+| datafusion.execution.parquet.writer_version |
1.0 | (writing) Sets parquet writer version valid values
are "1.0" and "2.0"
[...]
+| datafusion.execution.parquet.skip_arrow_metadata |
false | (writing) Skip encoding the embedded arrow metadata
in the KV_meta This is analogous to the
`ArrowWriterOptions::with_skip_arrow_metadata`. Refer to
<https://docs.rs/parquet/53.3.0/parquet/arrow/arrow_writer/struct.ArrowWriterOptions.html#method.with_skip_arrow_metadata>
[...]
+| datafusion.execution.parquet.compression |
zstd(3) | (writing) 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 Note that this default setting is not the same
as the default parquet writer setting.
[...]
+| datafusion.execution.parquet.dictionary_enabled |
true | (writing) Sets if dictionary encoding is enabled.
If NULL, uses default parquet writer setting
[...]
+| datafusion.execution.parquet.dictionary_page_size_limit |
1048576 | (writing) Sets best effort maximum dictionary page
size, in bytes
[...]
+| datafusion.execution.parquet.statistics_enabled |
page | (writing) 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.max_row_group_size |
1048576 | (writing) Target maximum number of rows in each row
group (defaults to 1M rows). Writing larger row groups requires more memory to
write, but can get better compression and be faster to read.
[...]
+| datafusion.execution.parquet.created_by |
datafusion version 51.0.0 | (writing) Sets "created by" property
[...]
+| datafusion.execution.parquet.column_index_truncate_length | 64
| (writing) Sets column index truncate length
[...]
+| datafusion.execution.parquet.statistics_truncate_length | 64
| (writing) Sets statistics truncate length. If NULL,
uses default parquet writer setting
[...]
+| datafusion.execution.parquet.data_page_row_count_limit |
20000 | (writing) Sets best effort maximum number of rows
in data page
[...]
+| datafusion.execution.parquet.encoding |
NULL | (writing) 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.bloom_filter_on_write |
false | (writing) Write bloom filters for all columns when
creating parquet files
[...]
+| datafusion.execution.parquet.bloom_filter_fpp |
NULL | (writing) Sets bloom filter false positive
probability. If NULL, uses default parquet writer setting
[...]
+| datafusion.execution.parquet.bloom_filter_ndv |
NULL | (writing) Sets bloom filter number of distinct
values. If NULL, uses default parquet writer setting
[...]
+| datafusion.execution.parquet.allow_single_file_parallelism |
true | (writing) Controls whether DataFusion will attempt
to speed up writing parquet files by serializing them in parallel. Each column
in each row group in each output file are serialized in parallel leveraging a
maximum possible core count of n_files*n_row_groups*n_columns.
[...]
+| datafusion.execution.parquet.maximum_parallel_row_group_writers | 1
| (writing) By default parallel parquet writer is tuned
for minimum memory usage in a streaming execution plan. You may see a
performance benefit when writing large parquet files by increasing
maximum_parallel_row_group_writers and
maximum_buffered_record_batches_per_stream if your system has idle cores and
can tolerate additional memory usage. Boosting these values is likely
worthwhile [...]
+| datafusion.execution.parquet.maximum_buffered_record_batches_per_stream | 2
| (writing) By default parallel parquet writer is tuned
for minimum memory usage in a streaming execution plan. You may see a
performance benefit when writing large parquet files by increasing
maximum_parallel_row_group_writers and
maximum_buffered_record_batches_per_stream if your system has idle cores and
can tolerate additional memory usage. Boosting these values is likely
worthwhile [...]
+| datafusion.execution.planning_concurrency | 0
| 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.skip_physical_aggregate_schema_check |
false | When set to true, skips verifying that the schema
produced by planning the input of `LogicalPlan::Aggregate` exactly matches the
schema of the input plan. When set to false, if the schema does not match
exactly (including nullability and metadata), a planning error will be raised.
This is used to workaround bugs in the planner that are now caught by the new
schema verification step. [...]
+| datafusion.execution.spill_compression |
uncompressed | Sets the compression codec used when spilling data
to disk. Since datafusion writes spill files using the Arrow IPC Stream format,
only codecs supported by the Arrow IPC Stream Writer are allowed. Valid values
are: uncompressed, lz4_frame, zstd. Note: lz4_frame offers faster
(de)compression, but typically results in larger spill files. In contrast, zstd
achieves higher compression rati [...]
+| 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 [...]
+| 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.max_spill_file_size_bytes |
134217728 | Maximum size in bytes for individual spill files
before rotating to a new file. When operators spill data to disk (e.g.,
RepartitionExec), they write multiple batches to the same file until this size
limit is reached, then rotate to a new file. This reduces syscall overhead
compared to one-file-per-batch while preventing files from growing too large. A
larger value reduces file creatio [...]
+| datafusion.execution.meta_fetch_concurrency | 32
| Number of files to read in parallel when inferring
schema and statistics
[...]
+| datafusion.execution.minimum_parallel_output_files | 4
| Guarantees a minimum level of output files running in
parallel. RecordBatches will be distributed in round robin fashion to each
parallel writer. Each writer is closed and a new file opened once
soft_max_rows_per_output_file is reached.
[...]
+| datafusion.execution.soft_max_rows_per_output_file |
50000000 | Target number of rows in output files when writing
multiple. This is a soft max, so it can be exceeded slightly. There also will
be one file smaller than the limit if the total number of rows written is not
roughly divisible by the soft max
[...]
+| datafusion.execution.max_buffered_batches_per_output_file | 2
| This is the maximum number of RecordBatches buffered
for each output file being worked. Higher values can potentially give faster
write performance at the cost of higher peak memory consumption
[...]
+| datafusion.execution.listing_table_ignore_subdirectory |
true | Should sub directories be ignored when scanning
directories for data files. Defaults to true (ignores subdirectories),
consistent with Hive. Note that this setting does not affect reading
partitioned tables (e.g. `/table/year=2021/month=01/data.parquet`).
[...]
+| datafusion.execution.listing_table_factory_infer_partitions |
true | Should a `ListingTable` created through the
`ListingTableFactory` infer table partitions from Hive compliant directories.
Defaults to true (partition columns are inferred and will be represented in the
table schema).
[...]
+| datafusion.execution.enable_recursive_ctes |
true | Should DataFusion support recursive CTEs
[...]
+| datafusion.execution.split_file_groups_by_statistics |
false | Attempt to eliminate sorts by packing & sorting
files with non-overlapping statistics into the same file groups. Currently
experimental
[...]
+| datafusion.execution.keep_partition_by_columns |
false | Should DataFusion keep the columns used for
partition_by in the output RecordBatches
[...]
+| datafusion.execution.skip_partial_aggregation_probe_ratio_threshold |
0.8 | Aggregation ratio (number of distinct groups /
number of input rows) threshold for skipping partial aggregation. If the value
is greater then partial aggregation will skip aggregation for further input
[...]
+| datafusion.execution.skip_partial_aggregation_probe_rows_threshold |
100000 | Number of input rows partial aggregation partition
should process, before aggregation ratio check and trying to switch to skipping
aggregation mode
[...]
+| datafusion.execution.use_row_number_estimates_to_optimize_partitioning |
false | Should DataFusion use row number estimates at the
input to decide whether increasing parallelism is beneficial or not. By
default, only exact row numbers (not estimates) are used for this decision.
Setting this flag to `true` will likely produce better plans. if the source of
statistics is accurate. We plan to make this the default in the future.
[...]
+| datafusion.execution.enforce_batch_size_in_joins |
false | Should DataFusion enforce batch size in joins or
not. By default, DataFusion will not enforce batch size in joins. Enforcing
batch size in joins can reduce memory usage when joining large tables with a
highly-selective join filter, but is also slightly slower.
[...]
+| datafusion.execution.objectstore_writer_buffer_size |
10485760 | Size (bytes) of data buffer DataFusion uses when
writing output files. This affects the size of the data chunks that are
uploaded to remote object stores (e.g. AWS S3). If very large (>= 100 GiB)
output files are being written, it may be necessary to increase this size to
avoid errors from the remote end point.
[...]
+| datafusion.execution.enable_ansi_mode |
false | Whether to enable ANSI SQL mode. The flag is
experimental and relevant only for DataFusion Spark built-in functions When
`enable_ansi_mode` is set to `true`, the query engine follows ANSI SQL
semantics for expressions, casting, and error handling. This means: - **Strict
type coercion rules:** implicit casts between incompatible types are
disallowed. - **Standard SQL arithmetic behavior [...]
+| datafusion.optimizer.enable_distinct_aggregation_soft_limit |
true | When set to true, the optimizer will push a limit
operation into grouped aggregations which have no aggregate expressions, as a
soft limit, emitting groups once the limit is reached, before all rows in the
group are read.
[...]
+| 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.enable_window_limits |
true | When set to true, the optimizer will attempt to
push limit operations past window functions, if possible
[...]
+| datafusion.optimizer.enable_topk_dynamic_filter_pushdown |
true | When set to true, the optimizer will attempt to
push down TopK dynamic filters into the file scan phase.
[...]
+| datafusion.optimizer.enable_join_dynamic_filter_pushdown |
true | When set to true, the optimizer will attempt to
push down Join dynamic filters into the file scan phase.
[...]
+| datafusion.optimizer.enable_dynamic_filter_pushdown |
true | When set to true attempts to push down dynamic
filters generated by operators (topk & join) into the file scan phase. For
example, for a query such as `SELECT * FROM t ORDER BY timestamp DESC LIMIT
10`, the optimizer will attempt to push down the current top 10 timestamps that
the TopK operator references into the file scans. This means that if we already
have 10 timestamps in the year [...]
+| 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.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_joins |
true | Should DataFusion repartition data using the join
keys to execute joins in parallel using the provided `target_partitions` level
[...]
+| 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 execut [...]
+| datafusion.optimizer.repartition_file_scans |
true | When set to `true`, datasource partitions will be
repartitioned to achieve maximum parallelism. This applies to both in-memory
partitions and FileSource's file groups (1 group is 1 partition). For
FileSources, only Parquet and CSV formats are currently supported. If set to
`true` for a FileSource, all files will be repartitioned evenly (i.e., a single
large file might be partitioned in [...]
+| 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.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 enviro [...]
+| datafusion.optimizer.prefer_existing_sort |
false | When true, DataFusion will opportunistically remove
sorts when the data is already sorted, (i.e. setting `preserve_order` to true
on `RepartitionExec` and using `SortPreservingMergeExec`) When false,
DataFusion will maximize plan parallelism using `RepartitionExec` even if this
requires subsequently resorting data using a `SortExec`.
[...]
+| 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.max_passes | 3
| Number of times that the optimizer will attempt to
optimize the plan
[...]
+| 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.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.enable_piecewise_merge_join |
false | When set to true, piecewise merge join is enabled.
PiecewiseMergeJoin is currently experimental. Physical planner will opt for
PiecewiseMergeJoin when there is only one range filter.
[...]
+| 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.hash_join_single_partition_threshold_rows |
131072 | The maximum estimated size in rows for one input
side of a HashJoin will be collected into a single partition
[...]
+| datafusion.optimizer.default_filter_selectivity | 20
| The default filter selectivity used by Filter
Statistics when an exact selectivity cannot be determined. Valid values are
between 0 (no selectivity) and 100 (all rows are selected).
[...]
+| datafusion.optimizer.prefer_existing_union |
false | When set to true, the optimizer will not attempt to
convert Union to Interleave
[...]
+| datafusion.optimizer.expand_views_at_output |
false | When set to true, if the returned type is a view
type then the output will be coerced to a non-view. Coerces `Utf8View` to
`LargeUtf8`, and `BinaryView` to `LargeBinary`.
[...]
+| 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.explain.show_sizes |
true | When set to true, the explain statement will print
the partition sizes
[...]
+| datafusion.explain.show_schema |
false | When set to true, the explain statement will print
schema information
[...]
+| datafusion.explain.format |
indent | Display format of explain. Default is "indent".
When set to "tree", it will print the plan in a tree-rendered format.
[...]
+| datafusion.explain.tree_maximum_render_width |
240 | (format=tree only) Maximum total width of the
rendered tree. When set to 0, the tree will have no width limit.
[...]
+| datafusion.explain.analyze_level |
dev | Verbosity level for "EXPLAIN ANALYZE". Default is
"dev" "summary" shows common metrics for high-level insights. "dev" provides
deep operator-level introspection for developers.
[...]
+| datafusion.sql_parser.parse_float_as_decimal |
false | When set to true, SQL parser will parse float as
decimal type
[...]
+| 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.enable_options_value_normalization |
false | When set to true, SQL parser will normalize options
value (convert value to lowercase). Note that this option is ignored and will
be removed in the future. All case-insensitive values are normalized
automatically.
[...]
+| 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, Ansi, DuckDB and Databricks.
[...]
+| datafusion.sql_parser.support_varchar_with_length |
true | If true, permit lengths for `VARCHAR` such as
`VARCHAR(20)`, but ignore the length. If false, error if a `VARCHAR` with a
length is specified. The Arrow type system does not have a notion of maximum
string length and thus DataFusion can not enforce such limits.
[...]
+| datafusion.sql_parser.map_string_types_to_utf8view |
true | If true, string types (VARCHAR, CHAR, Text, and
String) are mapped to `Utf8View` during SQL planning. If false, they are mapped
to `Utf8`. Default is true.
[...]
+| datafusion.sql_parser.collect_spans |
false | When set to true, the source locations relative to
the original SQL query (i.e.
[`Span`](https://docs.rs/sqlparser/latest/sqlparser/tokenizer/struct.Span.html))
will be collected and recorded in the logical plan nodes.
[...]
+| datafusion.sql_parser.recursion_limit | 50
| Specifies the recursion depth limit when parsing
complex SQL Queries
[...]
+| datafusion.sql_parser.default_null_ordering |
nulls_max | Specifies the default null ordering for query
results. There are 4 options: - `nulls_max`: Nulls appear last in ascending
order. - `nulls_min`: Nulls appear first in ascending order. - `nulls_first`:
Nulls always be first in any order. - `nulls_last`: Nulls always be last in any
order. By default, `nulls_max` is used to follow Postgres's behavior. postgres
rule: <https://www.postgresql [...]
+| datafusion.format.safe |
true | If set to `true` any formatting errors will be
written to the output instead of being converted into a [`std::fmt::Error`]
[...]
+| datafusion.format.null |
| Format string for nulls
[...]
+| datafusion.format.date_format |
%Y-%m-%d | Date format for date arrays
[...]
+| datafusion.format.datetime_format |
%Y-%m-%dT%H:%M:%S%.f | Format for DateTime arrays
[...]
+| datafusion.format.timestamp_format |
%Y-%m-%dT%H:%M:%S%.f | Timestamp format for timestamp arrays
[...]
+| datafusion.format.timestamp_tz_format |
NULL | Timestamp format for timestamp with timezone
arrays. When `None`, ISO 8601 format is used.
[...]
+| datafusion.format.time_format |
%H:%M:%S%.f | Time format for time arrays
[...]
+| datafusion.format.duration_format |
pretty | Duration format. Can be either `"pretty"` or
`"ISO8601"`
[...]
+| datafusion.format.types_info |
false | Show types in visual representation batches
[...]
# Runtime Configuration Settings
diff --git a/searchindex.js b/searchindex.js
index a7ca78a04c..365d486472 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles":{"!=":[[60,"op-neq"]],"!~":[[60,"op-re-not-match"]],"!~*":[[60,"op-re-not-match-i"]],"!~~":[[60,"id19"]],"!~~*":[[60,"id20"]],"#":[[60,"op-bit-xor"]],"%":[[60,"op-modulo"]],"&":[[60,"op-bit-and"]],"(relation,
name) tuples in logical fields and logical columns are
unique":[[13,"relation-name-tuples-in-logical-fields-and-logical-columns-are-unique"]],"*":[[60,"op-multiply"]],"+":[[60,"op-plus"]],"-":[[60,"op-minus"]],"/":[[60,"op-divide"]],"<":[[60,"op-lt"]],"<
[...]
\ No newline at end of file
+Search.setIndex({"alltitles":{"!=":[[60,"op-neq"]],"!~":[[60,"op-re-not-match"]],"!~*":[[60,"op-re-not-match-i"]],"!~~":[[60,"id19"]],"!~~*":[[60,"id20"]],"#":[[60,"op-bit-xor"]],"%":[[60,"op-modulo"]],"&":[[60,"op-bit-and"]],"(relation,
name) tuples in logical fields and logical columns are
unique":[[13,"relation-name-tuples-in-logical-fields-and-logical-columns-are-unique"]],"*":[[60,"op-multiply"]],"+":[[60,"op-plus"]],"-":[[60,"op-minus"]],"/":[[60,"op-divide"]],"<":[[60,"op-lt"]],"<
[...]
\ No newline at end of file
diff --git a/user-guide/configs.html b/user-guide/configs.html
index 40a3cb7a0e..301080bd09 100644
--- a/user-guide/configs.html
+++ b/user-guide/configs.html
@@ -701,211 +701,215 @@ example, to configure <code class="docutils literal
notranslate"><span class="pr
<td><p>10485760</p></td>
<td><p>Size (bytes) of data buffer DataFusion uses when writing output files.
This affects the size of the data chunks that are uploaded to remote object
stores (e.g. AWS S3). If very large (>= 100 GiB) output files are being
written, it may be necessary to increase this size to avoid errors from the
remote end point.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.enable_distinct_aggregation_soft_limit</p></td>
+<tr class="row-even"><td><p>datafusion.execution.enable_ansi_mode</p></td>
+<td><p>false</p></td>
+<td><p>Whether to enable ANSI SQL mode. The flag is experimental and relevant
only for DataFusion Spark built-in functions When <code class="docutils literal
notranslate"><span class="pre">enable_ansi_mode</span></code> is set to <code
class="docutils literal notranslate"><span class="pre">true</span></code>, the
query engine follows ANSI SQL semantics for expressions, casting, and error
handling. This means: - <strong>Strict type coercion rules:</strong> implicit
casts between incompati [...]
+</tr>
+<tr
class="row-odd"><td><p>datafusion.optimizer.enable_distinct_aggregation_soft_limit</p></td>
<td><p>true</p></td>
<td><p>When set to true, the optimizer will push a limit operation into
grouped aggregations which have no aggregate expressions, as a soft limit,
emitting groups once the limit is reached, before all rows in the group are
read.</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.enable_round_robin_repartition</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.enable_round_robin_repartition</p></td>
<td><p>true</p></td>
<td><p>When set to true, the physical plan optimizer will try to add round
robin repartitioning to increase parallelism to leverage more CPU cores</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.enable_topk_aggregation</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.enable_topk_aggregation</p></td>
<td><p>true</p></td>
<td><p>When set to true, the optimizer will attempt to perform limit
operations during aggregations, if possible</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.enable_window_limits</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.enable_window_limits</p></td>
<td><p>true</p></td>
<td><p>When set to true, the optimizer will attempt to push limit operations
past window functions, if possible</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.enable_topk_dynamic_filter_pushdown</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.enable_topk_dynamic_filter_pushdown</p></td>
<td><p>true</p></td>
<td><p>When set to true, the optimizer will attempt to push down TopK dynamic
filters into the file scan phase.</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.enable_join_dynamic_filter_pushdown</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.enable_join_dynamic_filter_pushdown</p></td>
<td><p>true</p></td>
<td><p>When set to true, the optimizer will attempt to push down Join dynamic
filters into the file scan phase.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.enable_dynamic_filter_pushdown</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.enable_dynamic_filter_pushdown</p></td>
<td><p>true</p></td>
<td><p>When set to true attempts to push down dynamic filters generated by
operators (topk & join) into the file scan phase. For example, for a query
such as <code class="docutils literal notranslate"><span
class="pre">SELECT</span> <span class="pre">*</span> <span
class="pre">FROM</span> <span class="pre">t</span> <span
class="pre">ORDER</span> <span class="pre">BY</span> <span
class="pre">timestamp</span> <span class="pre">DESC</span> <span
class="pre">LIMIT</span> <span class="pre [...]
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.filter_null_join_keys</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.filter_null_join_keys</p></td>
<td><p>false</p></td>
<td><p>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.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.repartition_aggregations</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.repartition_aggregations</p></td>
<td><p>true</p></td>
<td><p>Should DataFusion repartition data using the aggregate keys to execute
aggregates in parallel using the provided <code class="docutils literal
notranslate"><span class="pre">target_partitions</span></code> level</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.repartition_file_min_size</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.repartition_file_min_size</p></td>
<td><p>10485760</p></td>
<td><p>Minimum total files size in bytes to perform file scan
repartitioning.</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.optimizer.repartition_joins</p></td>
+<tr class="row-odd"><td><p>datafusion.optimizer.repartition_joins</p></td>
<td><p>true</p></td>
<td><p>Should DataFusion repartition data using the join keys to execute joins
in parallel using the provided <code class="docutils literal notranslate"><span
class="pre">target_partitions</span></code> level</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.allow_symmetric_joins_without_pruning</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.allow_symmetric_joins_without_pruning</p></td>
<td><p>true</p></td>
<td><p>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 runne [...]
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.repartition_file_scans</p></td>
+<tr class="row-odd"><td><p>datafusion.optimizer.repartition_file_scans</p></td>
<td><p>true</p></td>
<td><p>When set to <code class="docutils literal notranslate"><span
class="pre">true</span></code>, datasource partitions will be repartitioned to
achieve maximum parallelism. This applies to both in-memory partitions and
FileSource’s file groups (1 group is 1 partition). For FileSources, only
Parquet and CSV formats are currently supported. If set to <code
class="docutils literal notranslate"><span class="pre">true</span></code> for a
FileSource, all files will be repartitioned evenly ( [...]
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.repartition_windows</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.repartition_windows</p></td>
<td><p>true</p></td>
<td><p>Should DataFusion repartition data using the partitions keys to execute
window functions in parallel using the provided <code class="docutils literal
notranslate"><span class="pre">target_partitions</span></code> level</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.optimizer.repartition_sorts</p></td>
+<tr class="row-odd"><td><p>datafusion.optimizer.repartition_sorts</p></td>
<td><p>true</p></td>
<td><p>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 <code class="docutils literal
notranslate"><span class="pre">text</span> <span
class="pre">"SortExec:</span> <span class="pre">[a@0</span> <span
class="pre">ASC]",</span> <span class="pre">"</span> <span
class="pre">CoalescePartitionsExec",</span> <span
class="pre">"</span> [...]
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.prefer_existing_sort</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.prefer_existing_sort</p></td>
<td><p>false</p></td>
<td><p>When true, DataFusion will opportunistically remove sorts when the data
is already sorted, (i.e. setting <code class="docutils literal
notranslate"><span class="pre">preserve_order</span></code> to true on <code
class="docutils literal notranslate"><span
class="pre">RepartitionExec</span></code> and using <code class="docutils
literal notranslate"><span class="pre">SortPreservingMergeExec</span></code>)
When false, DataFusion will maximize plan parallelism using <code class="docut
[...]
</tr>
-<tr class="row-even"><td><p>datafusion.optimizer.skip_failed_rules</p></td>
+<tr class="row-odd"><td><p>datafusion.optimizer.skip_failed_rules</p></td>
<td><p>false</p></td>
<td><p>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</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.max_passes</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.max_passes</p></td>
<td><p>3</p></td>
<td><p>Number of times that the optimizer will attempt to optimize the
plan</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.top_down_join_key_reordering</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.top_down_join_key_reordering</p></td>
<td><p>true</p></td>
<td><p>When set to true, the physical plan optimizer will run a top down
process to reorder the join keys</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.prefer_hash_join</p></td>
+<tr class="row-even"><td><p>datafusion.optimizer.prefer_hash_join</p></td>
<td><p>true</p></td>
<td><p>When set to true, the physical plan optimizer will prefer HashJoin over
SortMergeJoin. HashJoin can work more efficiently than SortMergeJoin but
consumes more memory</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.enable_piecewise_merge_join</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.enable_piecewise_merge_join</p></td>
<td><p>false</p></td>
<td><p>When set to true, piecewise merge join is enabled. PiecewiseMergeJoin
is currently experimental. Physical planner will opt for PiecewiseMergeJoin
when there is only one range filter.</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.hash_join_single_partition_threshold</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.hash_join_single_partition_threshold</p></td>
<td><p>1048576</p></td>
<td><p>The maximum estimated size in bytes for one input side of a HashJoin
will be collected into a single partition</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.optimizer.hash_join_single_partition_threshold_rows</p></td>
+<tr
class="row-odd"><td><p>datafusion.optimizer.hash_join_single_partition_threshold_rows</p></td>
<td><p>131072</p></td>
<td><p>The maximum estimated size in rows for one input side of a HashJoin
will be collected into a single partition</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.optimizer.default_filter_selectivity</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.default_filter_selectivity</p></td>
<td><p>20</p></td>
<td><p>The default filter selectivity used by Filter Statistics when an exact
selectivity cannot be determined. Valid values are between 0 (no selectivity)
and 100 (all rows are selected).</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.optimizer.prefer_existing_union</p></td>
+<tr class="row-odd"><td><p>datafusion.optimizer.prefer_existing_union</p></td>
<td><p>false</p></td>
<td><p>When set to true, the optimizer will not attempt to convert Union to
Interleave</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.optimizer.expand_views_at_output</p></td>
+<tr
class="row-even"><td><p>datafusion.optimizer.expand_views_at_output</p></td>
<td><p>false</p></td>
<td><p>When set to true, if the returned type is a view type then the output
will be coerced to a non-view. Coerces <code class="docutils literal
notranslate"><span class="pre">Utf8View</span></code> to <code class="docutils
literal notranslate"><span class="pre">LargeUtf8</span></code>, and <code
class="docutils literal notranslate"><span class="pre">BinaryView</span></code>
to <code class="docutils literal notranslate"><span
class="pre">LargeBinary</span></code>.</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.explain.logical_plan_only</p></td>
+<tr class="row-odd"><td><p>datafusion.explain.logical_plan_only</p></td>
<td><p>false</p></td>
<td><p>When set to true, the explain statement will only print logical
plans</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.explain.physical_plan_only</p></td>
+<tr class="row-even"><td><p>datafusion.explain.physical_plan_only</p></td>
<td><p>false</p></td>
<td><p>When set to true, the explain statement will only print physical
plans</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.explain.show_statistics</p></td>
+<tr class="row-odd"><td><p>datafusion.explain.show_statistics</p></td>
<td><p>false</p></td>
<td><p>When set to true, the explain statement will print operator statistics
for physical plans</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.explain.show_sizes</p></td>
+<tr class="row-even"><td><p>datafusion.explain.show_sizes</p></td>
<td><p>true</p></td>
<td><p>When set to true, the explain statement will print the partition
sizes</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.explain.show_schema</p></td>
+<tr class="row-odd"><td><p>datafusion.explain.show_schema</p></td>
<td><p>false</p></td>
<td><p>When set to true, the explain statement will print schema
information</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.explain.format</p></td>
+<tr class="row-even"><td><p>datafusion.explain.format</p></td>
<td><p>indent</p></td>
<td><p>Display format of explain. Default is “indent”. When set to “tree”, it
will print the plan in a tree-rendered format.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.explain.tree_maximum_render_width</p></td>
+<tr
class="row-odd"><td><p>datafusion.explain.tree_maximum_render_width</p></td>
<td><p>240</p></td>
<td><p>(format=tree only) Maximum total width of the rendered tree. When set
to 0, the tree will have no width limit.</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.explain.analyze_level</p></td>
+<tr class="row-even"><td><p>datafusion.explain.analyze_level</p></td>
<td><p>dev</p></td>
<td><p>Verbosity level for “EXPLAIN ANALYZE”. Default is “dev” “summary” shows
common metrics for high-level insights. “dev” provides deep operator-level
introspection for developers.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.sql_parser.parse_float_as_decimal</p></td>
+<tr
class="row-odd"><td><p>datafusion.sql_parser.parse_float_as_decimal</p></td>
<td><p>false</p></td>
<td><p>When set to true, SQL parser will parse float as decimal type</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.sql_parser.enable_ident_normalization</p></td>
+<tr
class="row-even"><td><p>datafusion.sql_parser.enable_ident_normalization</p></td>
<td><p>true</p></td>
<td><p>When set to true, SQL parser will normalize ident (convert ident to
lowercase when not quoted)</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.sql_parser.enable_options_value_normalization</p></td>
+<tr
class="row-odd"><td><p>datafusion.sql_parser.enable_options_value_normalization</p></td>
<td><p>false</p></td>
<td><p>When set to true, SQL parser will normalize options value (convert
value to lowercase). Note that this option is ignored and will be removed in
the future. All case-insensitive values are normalized automatically.</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.sql_parser.dialect</p></td>
+<tr class="row-even"><td><p>datafusion.sql_parser.dialect</p></td>
<td><p>generic</p></td>
<td><p>Configure the SQL dialect used by DataFusion’s parser; supported values
include: Generic, MySQL, PostgreSQL, Hive, SQLite, Snowflake, Redshift, MsSQL,
ClickHouse, BigQuery, Ansi, DuckDB and Databricks.</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.sql_parser.support_varchar_with_length</p></td>
+<tr
class="row-odd"><td><p>datafusion.sql_parser.support_varchar_with_length</p></td>
<td><p>true</p></td>
<td><p>If true, permit lengths for <code class="docutils literal
notranslate"><span class="pre">VARCHAR</span></code> such as <code
class="docutils literal notranslate"><span
class="pre">VARCHAR(20)</span></code>, but ignore the length. If false, error
if a <code class="docutils literal notranslate"><span
class="pre">VARCHAR</span></code> with a length is specified. The Arrow type
system does not have a notion of maximum string length and thus DataFusion can
not enforce such limits.</p></td>
</tr>
-<tr
class="row-odd"><td><p>datafusion.sql_parser.map_string_types_to_utf8view</p></td>
+<tr
class="row-even"><td><p>datafusion.sql_parser.map_string_types_to_utf8view</p></td>
<td><p>true</p></td>
<td><p>If true, string types (VARCHAR, CHAR, Text, and String) are mapped to
<code class="docutils literal notranslate"><span
class="pre">Utf8View</span></code> during SQL planning. If false, they are
mapped to <code class="docutils literal notranslate"><span
class="pre">Utf8</span></code>. Default is true.</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.sql_parser.collect_spans</p></td>
+<tr class="row-odd"><td><p>datafusion.sql_parser.collect_spans</p></td>
<td><p>false</p></td>
<td><p>When set to true, the source locations relative to the original SQL
query (i.e. <a class="reference external"
href="https://docs.rs/sqlparser/latest/sqlparser/tokenizer/struct.Span.html";><code
class="docutils literal notranslate"><span class="pre">Span</span></code></a>)
will be collected and recorded in the logical plan nodes.</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.sql_parser.recursion_limit</p></td>
+<tr class="row-even"><td><p>datafusion.sql_parser.recursion_limit</p></td>
<td><p>50</p></td>
<td><p>Specifies the recursion depth limit when parsing complex SQL
Queries</p></td>
</tr>
-<tr
class="row-even"><td><p>datafusion.sql_parser.default_null_ordering</p></td>
+<tr class="row-odd"><td><p>datafusion.sql_parser.default_null_ordering</p></td>
<td><p>nulls_max</p></td>
<td><p>Specifies the default null ordering for query results. There are 4
options: - <code class="docutils literal notranslate"><span
class="pre">nulls_max</span></code>: Nulls appear last in ascending order. -
<code class="docutils literal notranslate"><span
class="pre">nulls_min</span></code>: Nulls appear first in ascending order. -
<code class="docutils literal notranslate"><span
class="pre">nulls_first</span></code>: Nulls always be first in any order. -
<code class="docutils litera [...]
</tr>
-<tr class="row-odd"><td><p>datafusion.format.safe</p></td>
+<tr class="row-even"><td><p>datafusion.format.safe</p></td>
<td><p>true</p></td>
<td><p>If set to <code class="docutils literal notranslate"><span
class="pre">true</span></code> any formatting errors will be written to the
output instead of being converted into a [<code class="docutils literal
notranslate"><span class="pre">std::fmt::Error</span></code>]</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.format.null</p></td>
+<tr class="row-odd"><td><p>datafusion.format.null</p></td>
<td><p></p></td>
<td><p>Format string for nulls</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.format.date_format</p></td>
+<tr class="row-even"><td><p>datafusion.format.date_format</p></td>
<td><p>%Y-%m-%d</p></td>
<td><p>Date format for date arrays</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.format.datetime_format</p></td>
+<tr class="row-odd"><td><p>datafusion.format.datetime_format</p></td>
<td><p>%Y-%m-%dT%H:%M:%S%.f</p></td>
<td><p>Format for DateTime arrays</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.format.timestamp_format</p></td>
+<tr class="row-even"><td><p>datafusion.format.timestamp_format</p></td>
<td><p>%Y-%m-%dT%H:%M:%S%.f</p></td>
<td><p>Timestamp format for timestamp arrays</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.format.timestamp_tz_format</p></td>
+<tr class="row-odd"><td><p>datafusion.format.timestamp_tz_format</p></td>
<td><p>NULL</p></td>
<td><p>Timestamp format for timestamp with timezone arrays. When <code
class="docutils literal notranslate"><span class="pre">None</span></code>, ISO
8601 format is used.</p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.format.time_format</p></td>
+<tr class="row-even"><td><p>datafusion.format.time_format</p></td>
<td><p>%H:%M:%S%.f</p></td>
<td><p>Time format for time arrays</p></td>
</tr>
-<tr class="row-even"><td><p>datafusion.format.duration_format</p></td>
+<tr class="row-odd"><td><p>datafusion.format.duration_format</p></td>
<td><p>pretty</p></td>
<td><p>Duration format. Can be either <code class="docutils literal
notranslate"><span class="pre">"pretty"</span></code> or <code
class="docutils literal notranslate"><span
class="pre">"ISO8601"</span></code></p></td>
</tr>
-<tr class="row-odd"><td><p>datafusion.format.types_info</p></td>
+<tr class="row-even"><td><p>datafusion.format.types_info</p></td>
<td><p>false</p></td>
<td><p>Show types in visual representation batches</p></td>
</tr>
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
