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-comet.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 9f4d8301 Publish built docs triggered by
4f2a80d5c4ff47b60e2bfba66e7336a70ecd1e87
9f4d8301 is described below
commit 9f4d83014041f92d12d32380c7025838c110e4a5
Author: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
AuthorDate: Fri Nov 8 15:47:27 2024 +0000
Publish built docs triggered by 4f2a80d5c4ff47b60e2bfba66e7336a70ecd1e87
---
_sources/user-guide/compatibility.md.txt | 1 +
_sources/user-guide/configs.md.txt | 32 ++++++++++++++++----------------
searchindex.js | 2 +-
user-guide/compatibility.html | 28 ++++++++++++++++------------
user-guide/configs.html | 32 ++++++++++++++++----------------
5 files changed, 50 insertions(+), 45 deletions(-)
diff --git a/_sources/user-guide/compatibility.md.txt
b/_sources/user-guide/compatibility.md.txt
index 031322e9..10459d4d 100644
--- a/_sources/user-guide/compatibility.md.txt
+++ b/_sources/user-guide/compatibility.md.txt
@@ -123,6 +123,7 @@ The following cast operations are generally compatible with
Spark except for the
| decimal | long | |
| decimal | float | |
| decimal | double | |
+| decimal | string | There can be formatting differences in some case due to
Spark using scientific notation where Comet does not |
| string | boolean | |
| string | byte | |
| string | short | |
diff --git a/_sources/user-guide/configs.md.txt
b/_sources/user-guide/configs.md.txt
index 1618a034..dc97e3c5 100644
--- a/_sources/user-guide/configs.md.txt
+++ b/_sources/user-guide/configs.md.txt
@@ -26,14 +26,14 @@ Comet provides the following configuration settings.
| spark.comet.batchSize | The columnar batch size, i.e., the maximum number of
rows that a batch can contain. | 8192 |
| spark.comet.caseConversion.enabled | Java uses locale-specific rules when
converting strings to upper or lower case and Rust does not, so we disable
upper and lower by default. | false |
| spark.comet.cast.allowIncompatible | Comet is not currently fully compatible
with Spark for all cast operations. Set this config to true to allow them
anyway. See compatibility guide for more information. | false |
-| spark.comet.columnar.shuffle.async.enabled | Whether to enable asynchronous
shuffle for Arrow-based shuffle. By default, this config is false. | false |
-| spark.comet.columnar.shuffle.async.max.thread.num | Maximum number of
threads on an executor used for Comet async columnar shuffle. By default, this
config is 100. This is the upper bound of total number of shuffle threads per
executor. In other words, if the number of cores * the number of shuffle
threads per task `spark.comet.columnar.shuffle.async.thread.num` is larger than
this config. Comet will use this config as the number of shuffle threads per
executor instead. | 100 |
-| spark.comet.columnar.shuffle.async.thread.num | Number of threads used for
Comet async columnar shuffle per shuffle task. By default, this config is 3.
Note that more threads means more memory requirement to buffer shuffle data
before flushing to disk. Also, more threads may not always improve performance,
and should be set based on the number of cores available. | 3 |
-| spark.comet.columnar.shuffle.memory.factor | Fraction of Comet memory to be
allocated per executor process for Comet shuffle. Comet memory size is
specified by `spark.comet.memoryOverhead` or calculated by
`spark.comet.memory.overhead.factor` * `spark.executor.memory`. By default,
this config is 1.0. | 1.0 |
+| spark.comet.columnar.shuffle.async.enabled | Whether to enable asynchronous
shuffle for Arrow-based shuffle. | false |
+| spark.comet.columnar.shuffle.async.max.thread.num | Maximum number of
threads on an executor used for Comet async columnar shuffle. This is the upper
bound of total number of shuffle threads per executor. In other words, if the
number of cores * the number of shuffle threads per task
`spark.comet.columnar.shuffle.async.thread.num` is larger than this config.
Comet will use this config as the number of shuffle threads per executor
instead. | 100 |
+| spark.comet.columnar.shuffle.async.thread.num | Number of threads used for
Comet async columnar shuffle per shuffle task. Note that more threads means
more memory requirement to buffer shuffle data before flushing to disk. Also,
more threads may not always improve performance, and should be set based on the
number of cores available. | 3 |
+| spark.comet.columnar.shuffle.memory.factor | Fraction of Comet memory to be
allocated per executor process for Comet shuffle. Comet memory size is
specified by `spark.comet.memoryOverhead` or calculated by
`spark.comet.memory.overhead.factor` * `spark.executor.memory`. | 1.0 |
| spark.comet.convert.csv.enabled | When enabled, data from Spark (non-native)
CSV v1 and v2 scans will be converted to Arrow format. Note that to enable
native vectorized execution, both this config and 'spark.comet.exec.enabled'
need to be enabled. | false |
| spark.comet.convert.json.enabled | When enabled, data from Spark
(non-native) JSON v1 and v2 scans will be converted to Arrow format. Note that
to enable native vectorized execution, both this config and
'spark.comet.exec.enabled' need to be enabled. | false |
| spark.comet.convert.parquet.enabled | When enabled, data from Spark
(non-native) Parquet v1 and v2 scans will be converted to Arrow format. Note
that to enable native vectorized execution, both this config and
'spark.comet.exec.enabled' need to be enabled. | false |
-| spark.comet.debug.enabled | Whether to enable debug mode for Comet. By
default, this config is false. When enabled, Comet will do additional checks
for debugging purpose. For example, validating array when importing arrays from
JVM at native side. Note that these checks may be expensive in performance and
should only be enabled for debugging purpose. | false |
+| spark.comet.debug.enabled | Whether to enable debug mode for Comet. When
enabled, Comet will do additional checks for debugging purpose. For example,
validating array when importing arrays from JVM at native side. Note that these
checks may be expensive in performance and should only be enabled for debugging
purpose. | false |
| spark.comet.dppFallback.enabled | Whether to fall back to Spark for queries
that use DPP. | true |
| 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 [...]
@@ -42,13 +42,13 @@ Comet provides the following configuration settings.
| spark.comet.exec.broadcastHashJoin.enabled | Whether to enable
broadcastHashJoin by default. | true |
| spark.comet.exec.coalesce.enabled | Whether to enable coalesce by default. |
true |
| spark.comet.exec.collectLimit.enabled | Whether to enable collectLimit by
default. | true |
-| 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 true. | true |
+| 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. | true |
| spark.comet.exec.expand.enabled | Whether to enable expand by default. |
true |
| spark.comet.exec.filter.enabled | Whether to enable filter by default. |
true |
| spark.comet.exec.globalLimit.enabled | Whether to enable globalLimit by
default. | true |
| spark.comet.exec.hashJoin.enabled | Whether to enable hashJoin by default. |
true |
| spark.comet.exec.localLimit.enabled | Whether to enable localLimit by
default. | true |
-| 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.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. | 0.7 |
| spark.comet.exec.project.enabled | Whether to enable project by default. |
true |
| spark.comet.exec.replaceSortMergeJoin | Experimental feature to force Spark
to replace SortMergeJoin with ShuffledHashJoin for improved performance. This
feature is not stable yet. For more information, refer to the Comet Tuning
Guide (https://datafusion.apache.org/comet/user-guide/tuning.html). | false |
| spark.comet.exec.shuffle.codec | The codec of Comet native shuffle used to
compress shuffle data. Only zstd is supported. | zstd |
@@ -63,18 +63,18 @@ Comet provides the following configuration settings.
| spark.comet.explain.native.enabled | When this setting is enabled, Comet
will provide a tree representation of the native query plan before execution
and again after execution, with metrics. | false |
| spark.comet.explain.verbose.enabled | When this setting is enabled, Comet
will provide a verbose tree representation of the extended information. | false
|
| spark.comet.explainFallback.enabled | When this setting is enabled, Comet
will provide logging explaining the reason(s) why a query stage cannot be
executed natively. Set this to false to reduce the amount of logging. | false |
-| spark.comet.memory.overhead.factor | Fraction of executor memory to be
allocated as additional non-heap memory per executor process for Comet. Default
value is 0.2. | 0.2 |
+| spark.comet.memory.overhead.factor | Fraction of executor memory to be
allocated as additional non-heap memory per executor process for Comet. | 0.2 |
| spark.comet.memory.overhead.min | Minimum amount of additional memory to be
allocated per executor process for Comet, in MiB. | 402653184b |
| spark.comet.nativeLoadRequired | 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. | false |
-| spark.comet.parquet.enable.directBuffer | Whether to use Java direct byte
buffer when reading Parquet. By default, this is false | false |
-| spark.comet.parquet.read.io.adjust.readRange.skew | In the parallel reader,
if the read ranges submitted are skewed in sizes, this option will cause the
reader to break up larger read ranges into smaller ranges to reduce the skew.
This will result in a slightly larger number of connections opened to the file
system but may give improved performance. The option is off by default. | false
|
-| spark.comet.parquet.read.io.mergeRanges | When enabled the parallel reader
will try to merge ranges of data that are separated by less than
'comet.parquet.read.io.mergeRanges.delta' bytes. Longer continuous reads are
faster on cloud storage. The default behavior is to merge consecutive ranges. |
true |
+| spark.comet.parquet.enable.directBuffer | Whether to use Java direct byte
buffer when reading Parquet. | false |
+| spark.comet.parquet.read.io.adjust.readRange.skew | In the parallel reader,
if the read ranges submitted are skewed in sizes, this option will cause the
reader to break up larger read ranges into smaller ranges to reduce the skew.
This will result in a slightly larger number of connections opened to the file
system but may give improved performance. | false |
+| spark.comet.parquet.read.io.mergeRanges | When enabled the parallel reader
will try to merge ranges of data that are separated by less than
'comet.parquet.read.io.mergeRanges.delta' bytes. Longer continuous reads are
faster on cloud storage. | true |
| spark.comet.parquet.read.io.mergeRanges.delta | The delta in bytes between
consecutive read ranges below which the parallel reader will try to merge the
ranges. The default is 8MB. | 8388608 |
-| spark.comet.parquet.read.parallel.io.enabled | Whether to enable Comet's
parallel reader for Parquet files. The parallel reader reads ranges of
consecutive data in a file in parallel. It is faster for large files and row
groups but uses more resources. The parallel reader is enabled by default. |
true |
+| spark.comet.parquet.read.parallel.io.enabled | Whether to enable Comet's
parallel reader for Parquet files. The parallel reader reads ranges of
consecutive data in a file in parallel. It is faster for large files and row
groups but uses more resources. | true |
| spark.comet.parquet.read.parallel.io.thread-pool.size | The maximum number
of parallel threads the parallel reader will use in a single executor. For
executors configured with a smaller number of cores, use a smaller number. | 16
|
| spark.comet.regexp.allowIncompatible | Comet is not currently fully
compatible with Spark for all regular expressions. Set this config to true to
allow them anyway using Rust's regular expression engine. See compatibility
guide for more information. | false |
-| spark.comet.scan.enabled | Whether to enable native scans. When this is
turned on, Spark will use Comet to read supported data sources (currently only
Parquet is supported natively). 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. | true |
-| spark.comet.scan.preFetch.enabled | Whether to enable pre-fetching feature
of CometScan. By default is disabled. | false |
-| spark.comet.scan.preFetch.threadNum | 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. | 2 |
-| spark.comet.shuffle.preferDictionary.ratio | 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.exec.shuffle.mode` is `jvm`. | 10.0 |
+| spark.comet.scan.enabled | Whether to enable native scans. When this is
turned on, Spark will use Comet to read supported data sources (currently only
Parquet is supported natively). Note that to enable native vectorized
execution, both this config and 'spark.comet.exec.enabled' need to be enabled.
| true |
+| spark.comet.scan.preFetch.enabled | Whether to enable pre-fetching feature
of CometScan. | false |
+| spark.comet.scan.preFetch.threadNum | The number of threads running
pre-fetching for CometScan. Effective if spark.comet.scan.preFetch.enabled is
enabled. Note that more pre-fetching threads means more memory requirement to
store pre-fetched row groups. | 2 |
+| spark.comet.shuffle.preferDictionary.ratio | 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. Note that this config is only used when
`spark.comet.exec.shuffle.mode` is `jvm`. | 10.0 |
| spark.comet.sparkToColumnar.supportedOperatorList | A comma-separated list
of operators that will be converted to Arrow columnar format when
'spark.comet.sparkToColumnar.enabled' is true | Range,InMemoryTableScan |
diff --git a/searchindex.js b/searchindex.js
index 371c22d4..b42246fb 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"alltitles": {"1. Install Comet": [[9, "install-comet"]], "2.
Clone Spark and Apply Diff": [[9, "clone-spark-and-apply-diff"]], "3. Run Spark
SQL Tests": [[9, "run-spark-sql-tests"]], "ANSI mode": [[11, "ansi-mode"]],
"API Differences Between Spark Versions": [[0,
"api-differences-between-spark-versions"]], "ASF Links": [[10, null]], "Adding
Spark-side Tests for the New Expression": [[0,
"adding-spark-side-tests-for-the-new-expression"]], "Adding a New Expression":
[[0, [...]
\ No newline at end of file
+Search.setIndex({"alltitles": {"1. Install Comet": [[9, "install-comet"]], "2.
Clone Spark and Apply Diff": [[9, "clone-spark-and-apply-diff"]], "3. Run Spark
SQL Tests": [[9, "run-spark-sql-tests"]], "ANSI mode": [[11, "ansi-mode"]],
"API Differences Between Spark Versions": [[0,
"api-differences-between-spark-versions"]], "ASF Links": [[10, null]], "Adding
Spark-side Tests for the New Expression": [[0,
"adding-spark-side-tests-for-the-new-expression"]], "Adding a New Expression":
[[0, [...]
\ No newline at end of file
diff --git a/user-guide/compatibility.html b/user-guide/compatibility.html
index 8c39a118..a507ea84 100644
--- a/user-guide/compatibility.html
+++ b/user-guide/compatibility.html
@@ -649,51 +649,55 @@ Spark.</p></li>
<td><p>double</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>string</p></td>
+<tr class="row-odd"><td><p>decimal</p></td>
+<td><p>string</p></td>
+<td><p>There can be formatting differences in some case due to Spark using
scientific notation where Comet does not</p></td>
+</tr>
+<tr class="row-even"><td><p>string</p></td>
<td><p>boolean</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p>string</p></td>
+<tr class="row-odd"><td><p>string</p></td>
<td><p>byte</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>string</p></td>
+<tr class="row-even"><td><p>string</p></td>
<td><p>short</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p>string</p></td>
+<tr class="row-odd"><td><p>string</p></td>
<td><p>integer</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>string</p></td>
+<tr class="row-even"><td><p>string</p></td>
<td><p>long</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p>string</p></td>
+<tr class="row-odd"><td><p>string</p></td>
<td><p>binary</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>string</p></td>
+<tr class="row-even"><td><p>string</p></td>
<td><p>date</p></td>
<td><p>Only supports years between 262143 BC and 262142 AD</p></td>
</tr>
-<tr class="row-even"><td><p>date</p></td>
+<tr class="row-odd"><td><p>date</p></td>
<td><p>string</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>timestamp</p></td>
+<tr class="row-even"><td><p>timestamp</p></td>
<td><p>long</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p>timestamp</p></td>
+<tr class="row-odd"><td><p>timestamp</p></td>
<td><p>decimal</p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p>timestamp</p></td>
+<tr class="row-even"><td><p>timestamp</p></td>
<td><p>string</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p>timestamp</p></td>
+<tr class="row-odd"><td><p>timestamp</p></td>
<td><p>date</p></td>
<td><p></p></td>
</tr>
diff --git a/user-guide/configs.html b/user-guide/configs.html
index 8f23dce4..584cd3a6 100644
--- a/user-guide/configs.html
+++ b/user-guide/configs.html
@@ -346,19 +346,19 @@ under the License.
<td><p>false</p></td>
</tr>
<tr class="row-odd"><td><p>spark.comet.columnar.shuffle.async.enabled</p></td>
-<td><p>Whether to enable asynchronous shuffle for Arrow-based shuffle. By
default, this config is false.</p></td>
+<td><p>Whether to enable asynchronous shuffle for Arrow-based shuffle.</p></td>
<td><p>false</p></td>
</tr>
<tr
class="row-even"><td><p>spark.comet.columnar.shuffle.async.max.thread.num</p></td>
-<td><p>Maximum number of threads on an executor used for Comet async columnar
shuffle. By default, this config is 100. This is the upper bound of total
number of shuffle threads per executor. In other words, if the number of cores
* the number of shuffle threads per task <code class="docutils literal
notranslate"><span
class="pre">spark.comet.columnar.shuffle.async.thread.num</span></code> is
larger than this config. Comet will use this config as the number of shuffle
threads per executo [...]
+<td><p>Maximum number of threads on an executor used for Comet async columnar
shuffle. This is the upper bound of total number of shuffle threads per
executor. In other words, if the number of cores * the number of shuffle
threads per task <code class="docutils literal notranslate"><span
class="pre">spark.comet.columnar.shuffle.async.thread.num</span></code> is
larger than this config. Comet will use this config as the number of shuffle
threads per executor instead.</p></td>
<td><p>100</p></td>
</tr>
<tr
class="row-odd"><td><p>spark.comet.columnar.shuffle.async.thread.num</p></td>
-<td><p>Number of threads used for Comet async columnar shuffle per shuffle
task. By default, this config is 3. Note that more threads means more memory
requirement to buffer shuffle data before flushing to disk. Also, more threads
may not always improve performance, and should be set based on the number of
cores available.</p></td>
+<td><p>Number of threads used for Comet async columnar shuffle per shuffle
task. Note that more threads means more memory requirement to buffer shuffle
data before flushing to disk. Also, more threads may not always improve
performance, and should be set based on the number of cores available.</p></td>
<td><p>3</p></td>
</tr>
<tr class="row-even"><td><p>spark.comet.columnar.shuffle.memory.factor</p></td>
-<td><p>Fraction of Comet memory to be allocated per executor process for Comet
shuffle. Comet memory size is specified by <code class="docutils literal
notranslate"><span class="pre">spark.comet.memoryOverhead</span></code> or
calculated by <code class="docutils literal notranslate"><span
class="pre">spark.comet.memory.overhead.factor</span></code> * <code
class="docutils literal notranslate"><span
class="pre">spark.executor.memory</span></code>. By default, this config is
1.0.</p></td>
+<td><p>Fraction of Comet memory to be allocated per executor process for Comet
shuffle. Comet memory size is specified by <code class="docutils literal
notranslate"><span class="pre">spark.comet.memoryOverhead</span></code> or
calculated by <code class="docutils literal notranslate"><span
class="pre">spark.comet.memory.overhead.factor</span></code> * <code
class="docutils literal notranslate"><span
class="pre">spark.executor.memory</span></code>.</p></td>
<td><p>1.0</p></td>
</tr>
<tr class="row-odd"><td><p>spark.comet.convert.csv.enabled</p></td>
@@ -374,7 +374,7 @@ under the License.
<td><p>false</p></td>
</tr>
<tr class="row-even"><td><p>spark.comet.debug.enabled</p></td>
-<td><p>Whether to enable debug mode for Comet. By default, this config is
false. When enabled, Comet will do additional checks for debugging purpose. For
example, validating array when importing arrays from JVM at native side. Note
that these checks may be expensive in performance and should only be enabled
for debugging purpose.</p></td>
+<td><p>Whether to enable debug mode for Comet. When enabled, Comet will do
additional checks for debugging purpose. For example, validating array when
importing arrays from JVM at native side. Note that these checks may be
expensive in performance and should only be enabled for debugging
purpose.</p></td>
<td><p>false</p></td>
</tr>
<tr class="row-odd"><td><p>spark.comet.dppFallback.enabled</p></td>
@@ -410,7 +410,7 @@ under the License.
<td><p>true</p></td>
</tr>
<tr class="row-odd"><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 true.</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.</p></td>
<td><p>true</p></td>
</tr>
<tr class="row-even"><td><p>spark.comet.exec.expand.enabled</p></td>
@@ -434,7 +434,7 @@ under the License.
<td><p>true</p></td>
</tr>
<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>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.</p></td>
<td><p>0.7</p></td>
</tr>
<tr class="row-even"><td><p>spark.comet.exec.project.enabled</p></td>
@@ -494,7 +494,7 @@ under the License.
<td><p>false</p></td>
</tr>
<tr class="row-even"><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>Fraction of executor memory to be allocated as additional non-heap
memory per executor process for Comet.</p></td>
<td><p>0.2</p></td>
</tr>
<tr class="row-odd"><td><p>spark.comet.memory.overhead.min</p></td>
@@ -506,15 +506,15 @@ under the License.
<td><p>false</p></td>
</tr>
<tr class="row-odd"><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>Whether to use Java direct byte buffer when reading Parquet.</p></td>
<td><p>false</p></td>
</tr>
<tr
class="row-even"><td><p>spark.comet.parquet.read.io.adjust.readRange.skew</p></td>
-<td><p>In the parallel reader, if the read ranges submitted are skewed in
sizes, this option will cause the reader to break up larger read ranges into
smaller ranges to reduce the skew. This will result in a slightly larger number
of connections opened to the file system but may give improved performance. The
option is off by default.</p></td>
+<td><p>In the parallel reader, if the read ranges submitted are skewed in
sizes, this option will cause the reader to break up larger read ranges into
smaller ranges to reduce the skew. This will result in a slightly larger number
of connections opened to the file system but may give improved
performance.</p></td>
<td><p>false</p></td>
</tr>
<tr class="row-odd"><td><p>spark.comet.parquet.read.io.mergeRanges</p></td>
-<td><p>When enabled the parallel reader will try to merge ranges of data that
are separated by less than ‘comet.parquet.read.io.mergeRanges.delta’ bytes.
Longer continuous reads are faster on cloud storage. The default behavior is to
merge consecutive ranges.</p></td>
+<td><p>When enabled the parallel reader will try to merge ranges of data that
are separated by less than ‘comet.parquet.read.io.mergeRanges.delta’ bytes.
Longer continuous reads are faster on cloud storage.</p></td>
<td><p>true</p></td>
</tr>
<tr
class="row-even"><td><p>spark.comet.parquet.read.io.mergeRanges.delta</p></td>
@@ -522,7 +522,7 @@ under the License.
<td><p>8388608</p></td>
</tr>
<tr
class="row-odd"><td><p>spark.comet.parquet.read.parallel.io.enabled</p></td>
-<td><p>Whether to enable Comet’s parallel reader for Parquet files. The
parallel reader reads ranges of consecutive data in a file in parallel. It is
faster for large files and row groups but uses more resources. The parallel
reader is enabled by default.</p></td>
+<td><p>Whether to enable Comet’s parallel reader for Parquet files. The
parallel reader reads ranges of consecutive data in a file in parallel. It is
faster for large files and row groups but uses more resources.</p></td>
<td><p>true</p></td>
</tr>
<tr
class="row-even"><td><p>spark.comet.parquet.read.parallel.io.thread-pool.size</p></td>
@@ -534,19 +534,19 @@ under the License.
<td><p>false</p></td>
</tr>
<tr class="row-even"><td><p>spark.comet.scan.enabled</p></td>
-<td><p>Whether to enable native scans. When this is turned on, Spark will use
Comet to read supported data sources (currently only Parquet is supported
natively). 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>Whether to enable native scans. When this is turned on, Spark will use
Comet to read supported data sources (currently only Parquet is supported
natively). Note that to enable native vectorized execution, both this config
and ‘spark.comet.exec.enabled’ need to be enabled.</p></td>
<td><p>true</p></td>
</tr>
<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>Whether to enable pre-fetching feature of CometScan.</p></td>
<td><p>false</p></td>
</tr>
<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>The number of threads running pre-fetching for CometScan. Effective if
spark.comet.scan.preFetch.enabled is enabled. 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-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 <code
class="docutils literal notranslate"><span
class="pre">spark.comet.exec.shuffle.mode</span></code> is <code class= [...]
+<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. Note that
this config is only used when <code class="docutils literal notranslate"><span
class="pre">spark.comet.exec.shuffle.mode</span></code> is <code
class="docutils literal notranslate"><s [...]
<td><p>10.0</p></td>
</tr>
<tr
class="row-even"><td><p>spark.comet.sparkToColumnar.supportedOperatorList</p></td>
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
