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new 802186621d Publish built docs triggered by
89d22b4b5c62f26e6cc0fc86dfa631ada1f44567
802186621d is described below
commit 802186621dcbcc0c38920621776d97fb17dacd71
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Wed Jan 17 21:24:54 2024 +0000
Publish built docs triggered by 89d22b4b5c62f26e6cc0fc86dfa631ada1f44567
---
_sources/user-guide/configs.md.txt | 1 +
searchindex.js | 2 +-
user-guide/configs.html | 52 ++++++++++++++++++++------------------
3 files changed, 30 insertions(+), 25 deletions(-)
diff --git a/_sources/user-guide/configs.md.txt
b/_sources/user-guide/configs.md.txt
index 5e26e2b205..a812b74284 100644
--- a/_sources/user-guide/configs.md.txt
+++ b/_sources/user-guide/configs.md.txt
@@ -83,6 +83,7 @@ Environment variables are read during `SessionConfig`
initialisation so they mus
| 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.enable_recursive_ctes |
false | Should DataFusion support recursive CTEs Defaults
to false since this feature is a work in progress and may not behave as
expected
[...]
| 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
[...]
diff --git a/searchindex.js b/searchindex.js
index f4feed15ac..d68ea69b56 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["contributor-guide/architecture",
"contributor-guide/communication", "contributor-guide/index",
"contributor-guide/quarterly_roadmap", "contributor-guide/roadmap",
"contributor-guide/specification/index",
"contributor-guide/specification/invariants",
"contributor-guide/specification/output-field-name-semantic", "index",
"library-user-guide/adding-udfs", "library-user-guide/building-logical-plans",
"library-user-guide/catalogs", "library-user-guide/custom-tab [...]
\ No newline at end of file
+Search.setIndex({"docnames": ["contributor-guide/architecture",
"contributor-guide/communication", "contributor-guide/index",
"contributor-guide/quarterly_roadmap", "contributor-guide/roadmap",
"contributor-guide/specification/index",
"contributor-guide/specification/invariants",
"contributor-guide/specification/output-field-name-semantic", "index",
"library-user-guide/adding-udfs", "library-user-guide/building-logical-plans",
"library-user-guide/catalogs", "library-user-guide/custom-tab [...]
\ No newline at end of file
diff --git a/user-guide/configs.html b/user-guide/configs.html
index e0e2c232ac..b6ae640d60 100644
--- a/user-guide/configs.html
+++ b/user-guide/configs.html
@@ -600,99 +600,103 @@ Environment variables are read during <code
class="docutils literal notranslate"
<td><p>true</p></td>
<td><p>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. <code
class="docutils literal notranslate"><span
class="pre">/table/year=2021/month=01/data.parquet</span></code>).</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_recursive_ctes</p></td>
+<td><p>false</p></td>
+<td><p>Should DataFusion support recursive CTEs Defaults to false since this
feature is a work in progress and may not behave as expected</p></td>
+</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.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>, file groups will be repartitioned to achieve
maximum parallelism. Currently Parquet and CSV formats are supported. If set to
<code class="docutils literal notranslate"><span
class="pre">true</span></code>, all files will be repartitioned evenly (i.e., a
single large file might be partitioned into smaller chunks) for parallel
scanning. If set to <code class="docutils literal notranslate"><s [...]
</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.hash_join_single_partition_threshold</p></td>
+<tr
class="row-odd"><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-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.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.sql_parser.parse_float_as_decimal</p></td>
+<tr
class="row-even"><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-even"><td><p>datafusion.sql_parser.enable_ident_normalization</p></td>
+<tr
class="row-odd"><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-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, and Ansi.</p></td>
</tr>
