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new 801118ed Publish built docs triggered by
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801118ed is described below
commit 801118ed5b64aa32b8c1900e19d00e8fef79f11f
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Tue May 14 21:17:44 2024 +0000
Publish built docs triggered by 2bf7d12109ff2644855db357306fc752dccddc6e
---
_sources/user-guide/configs.md.txt | 1 -
searchindex.js | 2 +-
user-guide/configs.html | 32 ++++++++++++++------------------
3 files changed, 15 insertions(+), 20 deletions(-)
diff --git a/_sources/user-guide/configs.md.txt
b/_sources/user-guide/configs.md.txt
index 24f408a0..0204b0c5 100644
--- a/_sources/user-guide/configs.md.txt
+++ b/_sources/user-guide/configs.md.txt
@@ -35,7 +35,6 @@ Comet provides the following configuration settings.
| spark.comet.enabled | Whether to enable Comet extension for Spark. When this
is turned on, Spark will use Comet to read Parquet data source. Note that to
enable native vectorized execution, both this config and
'spark.comet.exec.enabled' need to be enabled. By default, this config is the
value of the env var `ENABLE_COMET` if set, or true otherwise. | true |
| spark.comet.exceptionOnDatetimeRebase | Whether to throw exception when
seeing dates/timestamps from the legacy hybrid (Julian + Gregorian) calendar.
Since Spark 3, dates/timestamps were written according to the Proleptic
Gregorian calendar. When this is true, Comet will throw exceptions when seeing
these dates/timestamps that were written by Spark version before 3.0. If this
is false, these dates/timestamps will be read as if they were written to the
Proleptic Gregorian calendar and w [...]
| spark.comet.exec.all.enabled | Whether to enable all Comet operators. By
default, this config is false. Note that this config precedes all separate
config 'spark.comet.exec.<operator_name>.enabled'. That being said, if this
config is enabled, separate configs are ignored. | false |
-| spark.comet.exec.all.expr.enabled | Whether to enable all Comet exprs. By
default, this config is false. Note that this config precedes all separate
config 'spark.comet.exec.<expr_name>.enabled'. That being said, if this config
is enabled, separate configs are ignored. | false |
| spark.comet.exec.enabled | Whether to enable Comet native vectorized
execution for Spark. This controls whether Spark should convert operators into
their Comet counterparts and execute them in native space. Note: each operator
is associated with a separate config in the format of
'spark.comet.exec.<operator_name>.enabled' at the moment, and both the config
and this need to be turned on, in order for the operator to be executed in
native. By default, this config is false. | false |
| spark.comet.exec.memoryFraction | The fraction of memory from Comet memory
overhead that the native memory manager can use for execution. The purpose of
this config is to set aside memory for untracked data structures, as well as
imprecise size estimation during memory acquisition. Default value is 0.7. |
0.7 |
| spark.comet.exec.shuffle.codec | The codec of Comet native shuffle used to
compress shuffle data. Only zstd is supported. | zstd |
diff --git a/searchindex.js b/searchindex.js
index 515c36b3..32a410b3 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"ANSI mode": [[5, "ansi-mode"]], "ASF Links":
[[4, null]], "Additional Info": [[1, "additional-info"]], "After your debugging
is done": [[1, "after-your-debugging-is-done"]], "Apache DataFusion Comet":
[[4, "apache-datafusion-comet"]], "Architecture": [[11, "architecture"]],
"Asking for Help": [[0, "asking-for-help"]], "Benchmark": [[2, "benchmark"]],
"Build & Test": [[2, "build-test"]], "Building From Source": [[9,
"building-from-source"]], "CLion": [[2, " [...]
\ No newline at end of file
+Search.setIndex({"alltitles": {"ANSI mode": [[5, "ansi-mode"]], "ASF Links":
[[4, null]], "Additional Info": [[1, "additional-info"]], "After your debugging
is done": [[1, "after-your-debugging-is-done"]], "Apache DataFusion Comet":
[[4, "apache-datafusion-comet"]], "Architecture": [[11, "architecture"]],
"Asking for Help": [[0, "asking-for-help"]], "Benchmark": [[2, "benchmark"]],
"Build & Test": [[2, "build-test"]], "Building From Source": [[9,
"building-from-source"]], "CLion": [[2, " [...]
\ No newline at end of file
diff --git a/user-guide/configs.html b/user-guide/configs.html
index 01dd6cf7..a82aee63 100644
--- a/user-guide/configs.html
+++ b/user-guide/configs.html
@@ -341,63 +341,59 @@ under the License.
<td><p>Whether to enable all Comet operators. By default, this config is
false. Note that this config precedes all separate config
‘spark.comet.exec.<operator_name>.enabled’. That being said, if this
config is enabled, separate configs are ignored.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.exec.all.expr.enabled</p></td>
-<td><p>Whether to enable all Comet exprs. By default, this config is false.
Note that this config precedes all separate config
‘spark.comet.exec.<expr_name>.enabled’. That being said, if this config
is enabled, separate configs are ignored.</p></td>
-<td><p>false</p></td>
-</tr>
-<tr class="row-odd"><td><p>spark.comet.exec.enabled</p></td>
+<tr class="row-even"><td><p>spark.comet.exec.enabled</p></td>
<td><p>Whether to enable Comet native vectorized execution for Spark. This
controls whether Spark should convert operators into their Comet counterparts
and execute them in native space. Note: each operator is associated with a
separate config in the format of
‘spark.comet.exec.<operator_name>.enabled’ at the moment, and both the
config and this need to be turned on, in order for the operator to be executed
in native. By default, this config is false.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.exec.memoryFraction</p></td>
+<tr class="row-odd"><td><p>spark.comet.exec.memoryFraction</p></td>
<td><p>The fraction of memory from Comet memory overhead that the native
memory manager can use for execution. The purpose of this config is to set
aside memory for untracked data structures, as well as imprecise size
estimation during memory acquisition. Default value is 0.7.</p></td>
<td><p>0.7</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.exec.shuffle.codec</p></td>
+<tr class="row-even"><td><p>spark.comet.exec.shuffle.codec</p></td>
<td><p>The codec of Comet native shuffle used to compress shuffle data. Only
zstd is supported.</p></td>
<td><p>zstd</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.exec.shuffle.enabled</p></td>
+<tr class="row-odd"><td><p>spark.comet.exec.shuffle.enabled</p></td>
<td><p>Whether to enable Comet native shuffle. By default, this config is
false. Note that this requires setting ‘spark.shuffle.manager’ to
‘org.apache.spark.sql.comet.execution.shuffle.CometShuffleManager’.
‘spark.shuffle.manager’ must be set before starting the Spark application and
cannot be changed during the application.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.explainFallback.enabled</p></td>
+<tr class="row-even"><td><p>spark.comet.explainFallback.enabled</p></td>
<td><p>When this setting is enabled, Comet will provide logging explaining the
reason(s) why a query stage cannot be executed natively.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.memory.overhead.factor</p></td>
+<tr class="row-odd"><td><p>spark.comet.memory.overhead.factor</p></td>
<td><p>Fraction of executor memory to be allocated as additional non-heap
memory per executor process for Comet. Default value is 0.2.</p></td>
<td><p>0.2</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.memory.overhead.min</p></td>
+<tr class="row-even"><td><p>spark.comet.memory.overhead.min</p></td>
<td><p>Minimum amount of additional memory to be allocated per executor
process for Comet, in MiB.</p></td>
<td><p>402653184b</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.nativeLoadRequired</p></td>
+<tr class="row-odd"><td><p>spark.comet.nativeLoadRequired</p></td>
<td><p>Whether to require Comet native library to load successfully when Comet
is enabled. If not, Comet will silently fallback to Spark when it fails to load
the native lib. Otherwise, an error will be thrown and the Spark job will be
aborted.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.parquet.enable.directBuffer</p></td>
+<tr class="row-even"><td><p>spark.comet.parquet.enable.directBuffer</p></td>
<td><p>Whether to use Java direct byte buffer when reading Parquet. By
default, this is false</p></td>
<td><p>false</p></td>
</tr>
-<tr
class="row-even"><td><p>spark.comet.rowToColumnar.supportedOperatorList</p></td>
+<tr
class="row-odd"><td><p>spark.comet.rowToColumnar.supportedOperatorList</p></td>
<td><p>A comma-separated list of row-based operators that will be converted to
columnar format when ‘spark.comet.rowToColumnar.enabled’ is true</p></td>
<td><p>Range,InMemoryTableScan</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.scan.enabled</p></td>
+<tr class="row-even"><td><p>spark.comet.scan.enabled</p></td>
<td><p>Whether to enable Comet scan. When this is turned on, Spark will use
Comet to read Parquet data source. Note that to enable native vectorized
execution, both this config and ‘spark.comet.exec.enabled’ need to be enabled.
By default, this config is true.</p></td>
<td><p>true</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.scan.preFetch.enabled</p></td>
+<tr class="row-odd"><td><p>spark.comet.scan.preFetch.enabled</p></td>
<td><p>Whether to enable pre-fetching feature of CometScan. By default is
disabled.</p></td>
<td><p>false</p></td>
</tr>
-<tr class="row-odd"><td><p>spark.comet.scan.preFetch.threadNum</p></td>
+<tr class="row-even"><td><p>spark.comet.scan.preFetch.threadNum</p></td>
<td><p>The number of threads running pre-fetching for CometScan. Effective if
spark.comet.scan.preFetch.enabled is enabled. By default it is 2. Note that
more pre-fetching threads means more memory requirement to store pre-fetched
row groups.</p></td>
<td><p>2</p></td>
</tr>
-<tr class="row-even"><td><p>spark.comet.shuffle.preferDictionary.ratio</p></td>
+<tr class="row-odd"><td><p>spark.comet.shuffle.preferDictionary.ratio</p></td>
<td><p>The ratio of total values to distinct values in a string column to
decide whether to prefer dictionary encoding when shuffling the column. If the
ratio is higher than this config, dictionary encoding will be used on shuffling
string column. This config is effective if it is higher than 1.0. By default,
this config is 10.0. Note that this config is only used when
‘spark.comet.columnar.shuffle.enabled’ is true.</p></td>
<td><p>10.0</p></td>
</tr>
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