Comet Configuration Settings

Comet provides the following configuration settings.

Config

Description

Default Value

spark.comet.batchSize

The columnar batch size, i.e., the maximum number of rows that a batch can contain.

8192

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.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.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 will not be rebased.

false

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.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

spark.comet.exec.shuffle.enabled

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.

false

spark.comet.exec.shuffle.mode

The mode of Comet shuffle. This config is only effective if Comet shuffle is enabled. Available modes are ‘native’, ‘jvm’, and ‘auto’. ‘native’ is for native shuffle which has best performance in general. ‘jvm’ is for jvm-based columnar shuffle which has higher coverage than native shuffle. ‘auto’ is for Comet to choose the best shuffle mode based on the query plan. By default, this config is ‘jvm’.

jvm

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.

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.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.rowToColumnar.supportedOperatorList

A comma-separated list of row-based operators that will be converted to columnar format when ‘spark.comet.rowToColumnar.enabled’ is true

Range,InMemoryTableScan

spark.comet.scan.enabled

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.

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.columnar.shuffle.enabled’ is true.

10.0

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