RAPIDS Accelerator for Apache Spark Configuration

The following is the list of options that rapids-plugin-4-spark supports.

On startup use: --conf [conf key]=[conf value]. For example:

${SPARK_HOME}/bin/spark-shell --jars rapids-4-spark_2.12-23.02.0-cuda11.jar \
--conf spark.plugins=com.nvidia.spark.SQLPlugin \
--conf spark.rapids.sql.concurrentGpuTasks=2

At runtime use: spark.conf.set("[conf key]", [conf value]). For example:

scala> spark.conf.set("spark.rapids.sql.concurrentGpuTasks", 2)

All configs can be set on startup, but some configs, especially for shuffle, will not work if they are set at runtime. Please check the column of “Applicable at” to see when the config can be set. “Startup” means only valid on startup, “Runtime” means valid on both startup and runtime.

General Configuration

Name	Description	Default Value	Applicable at
spark.rapi ds.alluxio.aut omount.enabled	Enable the feature of auto mounting the cloud storage to Alluxio. It requires the Alluxio master is the same node of Spark driver node. When it’s true, it requires an environment variable ALLUXIO_HOME be set properly. The default value of ALLUXIO_HOME is “/opt/a lluxio-2.8.0”. You can set it as an environment variable when running a spark-submit or you can use spark.ya rn.appMasterEn v.ALLUXIO_HOME to set it on Yarn. The Alluxio master’s host and port will be read from alluxio.m aster.hostname and allu xio.master.rpc .port(default: 19998) from ALLUXIO_HOME/c onf/alluxio-si te.properties, then replace a cloud path which matches spark .rapids.alluxi o.bucket.regex like “s 3://bar/b.csv” to “alluxio ://0.1.2.3:199 98/bar/b.csv”, and the bucket “s3://bar” will be mounted to “/bar” in Alluxio automatically.	false	Runtime
spark .rapids.alluxi o.bucket.regex	A regex to decide which bucket should be auto-mounted to Alluxio. E.g. when setting as “^s3 ://bucket.*”, the bucket which starts with “s3://bucket” will be mounted to Alluxio and the path “s3://buc ket-foo/a.csv” will be replaced to “ alluxio://0.1. 2.3:19998/buck et-foo/a.csv”. It’s only valid when setting sp ark.rapids.all uxio.automount .enabled=true. The default value matches all the buckets in “s3://” or “s3a://” scheme.	^ s3a{0,1}://.*	Runtime
spark.rapids. alluxio.large. file.threshold	The threshold is used to identify whether average size of files is large when reading from S3. If reading large files from S3 and the disks used by Alluxio are slow, directly reading from S3 is better than reading caches from Alluxio, because S3 network bandwidth is faster than local disk. This improvement takes effect when sp ark.rapids.all uxio.slow.disk is enabled.	67108864	Runtime
spark.r apids.alluxio. pathsToReplace	List of paths to be replaced with corresponding Alluxio scheme. E.g. when configure is set to “s3://fo o->alluxio://0 .1.2.3:19998/f oo,gs://bar->a lluxio://0.1.2 .3:19998/bar”, it means: “s 3://foo/a.csv” will be replaced to “alluxi o://0.1.2.3:19 998/foo/a.csv” and “g s://bar/b.csv” will be replaced to “alluxio ://0.1.2.3:199 98/bar/b.csv”. To use this config, you have to mount the buckets to Alluxio by yourself. If you set this config, spark.rapi ds.alluxio.aut omount.enabled won’t be valid.	None	Startup
spark.rap ids.alluxio.re placement.algo	The algorithm used when replacing the UFS path with the Alluxio path. CONVERT_TIME and TASK_TIME are the valid options. CONVERT_TIME indicates that we do it when we convert it to a GPU file read, this has extra overhead of creating an entirely new file index, which requires listing the files and getting all new file info from Alluxio. TASK_TIME replaces the path as late as possible inside of the task. By waiting and replacing it at task time, it just replaces the path without fetching the file information again, this is faster but doesn’t update locality information if that has a bit impact on performance.	TASK_TIME	Runtime
sp ark.rapids.all uxio.slow.disk	Indicates whether the disks used by Alluxio are slow. If it’s true and reading S3 large files, Rapids Accelerator reads from S3 directly instead of reading from Alluxio caches. Refer to spark.rapids. alluxio.large. file.threshold which defines a threshold that identifying whether files are large. Typically, it’s slow disks if speed is less than 300M/second. If using convert time spark.rapi ds.alluxio.rep lacement.algo, this may not apply to all file types like Delta files	true	Runtime
spark.rapid s.alluxio.user	Alluxio user is set on the Alluxio client, which is used to mount or get information. By default it should be the user that running the Alluxio processes. The default value is ubuntu.	ubuntu	Runtime
spark.rapid s.cloudSchemes	Comma separated list of additional URI schemes that are to be considered cloud based filesystems. Schemes already included: abfs, abfss, dbfs, gs, s3, s3a, s3n, wasbs. Cloud based stores generally would be total separate from the executors and likely have a higher I/O read cost. Many times the cloud filesystems also get better throughput when you have multiple readers in parallel. This is used with s park.rapids.sq l.format.parqu et.reader.type	None	Runtime
s park.rapids.gp u.resourceName	The name of the Spark resource that represents a GPU that you want the plugin to use if using custom resources with Spark.	gpu	Startup
spark.rap ids.memory.gpu .allocFraction	The fraction of available (free) GPU memory that should be allocated for pooled memory. This must be less than or equal to the maximum limit configured via spark.rapids. memory.gpu.max AllocFraction, and greater than or equal to the minimum limit configured via spark.rapids. memory.gpu.min AllocFraction.	1.0	Startup
s park.rapids.me mory.gpu.debug	Provides a log of GPU memory allocations and frees. If set to STDOUT or STDERR the logging will go there. Setting it to NONE disables logging. All other values are reserved for possible future expansion and in the mean time will disable logging.	NONE	Startup
spark.rapi ds.memory.gpu. direct.storage .spill.batchWr iteBuffer.size	The size of the GPU memory buffer used to batch small buffers when spilling to GDS. Note that this buffer is mapped to the PCI Base Address Register (BAR) space, which may be very limited on some GPUs (e.g. the NVIDIA T4 only has 256 MiB), and it is also used by UCX bounce buffers.	8388608	Startup
spark.rapi ds.memory.gpu. direct.storage .spill.enabled	Should GPUDirect Storage (GDS) be used to spill GPU memory buffers directly to disk. GDS must be enabled and the directory spa rk.local.dir must support GDS. This is an experimental feature. For more information on GDS, see h ttps://docs.nv idia.com/gpudi rect-storage/.	false	Startup
spark.rapids .memory.gpu.ma xAllocFraction	The fraction of total GPU memory that limits the maximum size of the RMM pool. The value must be greater than or equal to the setting for spark.rapi ds.memory.gpu. allocFraction. Note that this limit will be reduced by the reserve memory configured in spar k.rapids.memor y.gpu.reserve.	1.0	Startup
spark.rapids .memory.gpu.mi nAllocFraction	The fraction of total GPU memory that limits the minimum size of the RMM pool. The value must be less than or equal to the setting for spark.rapi ds.memory.gpu. allocFraction.	0.25	Startup
spark. rapids.memory. gpu.oomDumpDir	The path to a local directory where a heap dump will be created if the GPU encounters an unrecoverable out-of-memory (OOM) error. The filename will be of the form: “gp u-oom–.hprof” where is the process ID, and the dumpId is a sequence number to disambiguate multiple heap dumps per process lifecycle	None	Startup
spark.rapids.m emory.gpu.pool	Select the RMM pooling allocator to use. Valid values are “DEFAULT”, “ARENA”, “ASYNC”, and “NONE”. With “DEFAULT”, the RMM pool allocator is used; with “ARENA”, the RMM arena allocator is used; with “ASYNC”, the new CUDA stream-ordered memory allocator in CUDA 11.2+ is used. If set to “NONE”, pooling is disabled and RMM just passes through to CUDA memory allocation directly.	ASYNC	Startup
spark.rapid s.memory.gpu.p ooling.enabled	Should RMM act as a pooling allocator for GPU memory, or should it just pass through to CUDA memory allocation directly. DEPRECATED: please use spark.rapids.m emory.gpu.pool instead.	true	Startup
spa rk.rapids.memo ry.gpu.reserve	The amount of GPU memory that should remain unallocated by RMM and left for system use such as memory needed for kernels and kernel launches.	671088640	Startup
spark.rapid s.memory.gpu.u nspill.enabled	When a spilled GPU buffer is needed again, should it be unspilled, or only copied back into GPU memory temporarily. Unspilling may be useful for GPU buffers that are needed frequently, for example, broadcast variables; however, it may also increase GPU memory usage	false	Startup
spark.rapids.m emory.host.pag eablePool.size	The size of the pageable memory pool in bytes unless otherwise specified. Use 0 to disable the pool.	1073741824	Startup
spark.rapids. memory.host.sp illStorageSize	Amount of off-heap host memory to use for buffering spilled GPU data before spilling to local disk. Use -1 to set the amount to the combined size of pinned and pageable memory pools.	-1	Startup
spark.r apids.memory.p innedPool.size	The size of the pinned memory pool in bytes unless otherwise specified. Use 0 to disable the pool.	0	Startup
s park.rapids.py thon.concurren tPythonWorkers	Set the number of Python worker processes that can execute concurrently per GPU. Python worker processes may temporarily block when the number of concurrent Python worker processes started by the same executor exceeds this amount. Allowing too many concurrent tasks on the same GPU may lead to GPU out of memory errors. >0 means enabled, while <=0 means unlimited	0	Runtime
sp ark.rapids.pyt hon.memory.gpu .allocFraction	The fraction of total GPU memory that should be initially allocated for pooled memory for all the Python workers. It supposes to be less than (1 - $(spark.rapids .memory.gpu.al locFraction)), since the executor will share the GPU with its owning Python workers. Half of the rest will be used if not specified	None	Runtime
spark .rapids.python .memory.gpu.ma xAllocFraction	The fraction of total GPU memory that limits the maximum size of the RMM pool for all the Python workers. It supposes to be less than (1 - $(s park.rapids.me mory.gpu.maxAl locFraction)), since the executor will share the GPU with its owning Python workers. when setting to 0 it means no limit.	0.0	Runtime
spar k.rapids.pytho n.memory.gpu.p ooling.enabled	Should RMM in Python workers act as a pooling allocator for GPU memory, or should it just pass through to CUDA memory allocation directly. When not specified, It will honor the value of config ‘spark.rapids .memory.gpu.po oling.enabled’	None	Runtime
spark.rapids.s huffle.enabled	Enable or disable the RAPIDS Shuffle Manager at runtime. The RAPIDS Shuffle Ma nager must already be configured. When set to false, the built-in Spark shuffle will be used.	true	Runtime
spark.rapid s.shuffle.mode	RAPIDS Shuffle Manager mode. “M ULTITHREADED”: shuffle file writes and reads are parallelized using a thread pool. “UCX”: (requires UCX installation) uses accelerated transports for transferring shuffle blocks. “CACHE_ONLY”: use when running a single executor, for short-circuit cached shuffle (for testing purposes).	MULTITHREADED	Startup
spark.rap ids.shuffle.mu ltiThreaded.ma xBytesInFlight	The size limit, in bytes, that the RAPIDS shuffle manager configured in “ MULTITHREADED” mode will allow to be deserialized concurrently per task. This is also the maximum amount of memory that will be used per task. This should ideally be at least the same size as the batch size so we don’t have to wait to process a single batch.	2147483647	Startup
spark.r apids.shuffle. multiThreaded. reader.threads	The number of threads to use for reading shuffle blocks per executor in the RAPIDS shuffle manager configured in “ MULTITHREADED” mode. There are two special values: 0 = feature is disabled, falls back to Spark built-in shuffle reader; 1 = our implementation of Spark’s built-in shuffle reader with extra metrics.	20	Startup
spark.r apids.shuffle. multiThreaded. writer.threads	The number of threads to use for writing shuffle blocks per executor in the RAPIDS shuffle manager configured in “ MULTITHREADED” mode. There are two special values: 0 = feature is disabled, falls back to Spark built-in shuffle writer; 1 = our implementation of Spark’s built-in shuffle writer with extra metrics.	20	Startup
spark.rapids. shuffle.transp ort.earlyStart	Enable early connection establishment for RAPIDS Shuffle	true	Startup
spa rk.rapids.shuf fle.transport. earlyStart.hea rtbeatInterval	Shuffle early start heartbeat interval ( milliseconds). Executors will send a heartbeat RPC message to the driver at this interval	5000	Startup
sp ark.rapids.shu ffle.transport .earlyStart.he artbeatTimeout	Shuffle early start heartbeat timeout ( milliseconds). Executors that don’t heartbeat within this timeout will be considered stale. This timeout must be higher than the value for spa rk.rapids.shuf fle.transport. earlyStart.hea rtbeatInterval	10000	Startup
spark.rapids .shuffle.trans port.maxReceiv eInflightBytes	Maximum aggregate amount of bytes that be fetched at any given time from peers during shuffle	1073741824	Startup
spark.r apids.shuffle. ucx.activeMess ages.forceRndv	Set to true to force ‘rndv’ mode for all UCX Active Messages. This should only be required with UCX 1.10.x. UCX 1.11.x deployments should set to false.	false	Startup
spa rk.rapids.shuf fle.ucx.manage mentServerHost	The host to be used to start the management server	null	Startup
spark. rapids.shuffle .ucx.useWakeup	When set to true, use UCX’s event-based progress (epoll) in order to wake up the progress thread when needed, instead of a hot loop.	true	Startup
spa rk.rapids.sql. batchSizeBytes	Set the target number of bytes for a GPU batch. Splits sizes for input data is covered by separate configs. The maximum setting is 2 GB to avoid exceeding the cudf row count limit of a column.	2147483647	Runtime
s park.rapids.sq l.castDecimalT oFloat.enabled	Casting from decimal to floating point types on the GPU returns results that have tiny difference compared to results returned from CPU.	true	Runtime
sp ark.rapids.sql .castDecimalTo String.enabled	When set to true, casting from decimal to string is supported on the GPU. The GPU does NOT produce exact same string as spark produces, but producing strings which are semantically equal. For instance, given input B igDecimal(123, -2), the GPU produces “12300”, which spark produces “1.23E+4”.	false	Runtime
s park.rapids.sq l.castFloatToD ecimal.enabled	Casting from floating point types to decimal on the GPU returns results that have tiny difference compared to results returned from CPU.	true	Runtime
spark.r apids.sql.cast FloatToIntegra lTypes.enabled	Casting from floating point types to integral types on the GPU supports a slightly different range of values when using Spark 3.1.0 or later. Refer to the CAST documentation for more details.	true	Runtime
spark.rapids.s ql.castFloatTo String.enabled	Casting from floating point types to string on the GPU returns results that have a different precision than the default results of Spark.	true	Runtime
spark.rapids.s ql.castStringT oFloat.enabled	When set to true, enables casting from strings to float types (float, double) on the GPU. Currently hex values aren’t supported on the GPU. Also note that casting from string to float types on the GPU returns incorrect results when the string represents any number “1.7976931 348623158E308” <= x < “1.7976931 348623159E308” and “-1.7976931 348623158E308” >= x > “-1.7976931 348623159E308” in both these cases the GPU returns D ouble.MaxValue while CPU returns “+Infinity” and “-Infinity” respectively	true	Runtime
spar k.rapids.sql.c astStringToTim estamp.enabled	When set to true, casting from string to timestamp is supported on the GPU. The GPU only supports a subset of formats when casting strings to timestamps. Refer to the CAST documentation for more details.	false	Runtime
spark.rapi ds.sql.coalesc ing.reader.num FilterParallel	This controls the number of files the coalescing reader will run in each thread when it filters blocks for reading. If this value is greater than zero the files will be filtered in a multithreaded manner where each thread filters the number of files set by this config. If this is set to zero the files are filtered serially. This uses the same thread pool as the multithreaded reader, see spar k.rapids.sql.m ultiThreadedRe ad.numThreads. Note that filtering multithreaded is useful with Alluxio.	0	Runtime
spark.r apids.sql.conc urrentGpuTasks	Set the number of tasks that can execute concurrently per GPU. Tasks may temporarily block when the number of concurrent tasks in the executor exceeds this amount. Allowing too many concurrent tasks on the same GPU may lead to GPU out of memory errors.	1	Runtime
spark.rap ids.sql.concur rentWriterPart itionFlushSize	The flush size of the concurrent writer cache in bytes for each partition. If specified spark.sql.max ConcurrentOutp utFileWriters, use concurrent writer to write data. Concurrent writer first caches data for each partition and begins to flush the data if it finds one partition with a size that is greater than or equal to this config. The default value is 0, which will try to select a size based off of file type specific configs. E.g.: It uses write.pa rquet.row-grou p-size-bytes config for Parquet type and orc .stripe.size config for Orc type. If the value is greater than 0, will use this positive value.Max value may get better performance but not always, because concurrent writer uses spillable cache and big value may cause more IO swaps.	0	Runtime
spark.rapids. sql.csv.read.d ecimal.enabled	CSV reading is not 100% compatible when reading decimals.	false	Runtime
spark.rapids .sql.csv.read. double.enabled	CSV reading is not 100% compatible when reading doubles.	true	Runtime
spark.rapid s.sql.csv.read .float.enabled	CSV reading is not 100% compatible when reading floats.	true	Runtime
spark.rapids.s ql.decimalOver flowGuarantees	FOR TESTING ONLY. DO NOT USE IN PRODUCTION. Please see the decimal section of the compatibility documents for more information on this config.	true	Runtime
spa rk.rapids.sql. detectDeltaChe ckpointQueries	Queries against Delta Lake _delta_log checkpoint Parquet files are not efficient on the GPU. When this option is enabled, the plugin will attempt to detect these queries and fall back to the CPU.	true	Runtime
spark.rapi ds.sql.detectD eltaLogQueries	Queries against Delta Lake _delta_log JSON files are not efficient on the GPU. When this option is enabled, the plugin will attempt to detect these queries and fall back to the CPU.	true	Runtime
spark.rapi ds.sql.enabled	Enable (true) or disable (false) sql operations on the GPU	true	Runtime
spark.rapi ds.sql.explain	Explain why some parts of a query were not placed on a GPU or not. Possible values are ALL: print everything, NONE: print nothing, NOT_ON_GPU: print only parts of a query that did not go on the GPU	NOT_ON_GPU	Runtime
spark.rapids.s ql.fast.sample	Option to turn on fast sample. If enable it is inconsistent with CPU sample because of GPU sample algorithm is inconsistent with CPU.	false	Runtime
spark.ra pids.sql.forma t.avro.enabled	When set to true enables all avro input and output acceleration. (only input is currently supported anyways)	false	Runtime
spark.rapi ds.sql.format. avro.multiThre adedRead.maxNu mFilesParallel	A limit on the maximum number of files per task processed in parallel on the CPU side before the file is sent to the GPU. This affects the amount of host memory used when reading the files in parallel. Used with MULTITHREADED reader, see spark.rapids. sql.format.avr o.reader.type.	2147483647	Runtime
s park.rapids.sq l.format.avro. multiThreadedR ead.numThreads	The maximum number of threads, on one executor, to use for reading small Avro files in parallel. This can not be changed at runtime after the executor has started. Used with MULTITHREADED reader, see spark.rapids. sql.format.avr o.reader.type. DEPRECATED: use spa rk.rapids.sql. multiThreadedR ead.numThreads	None	Startup
spark.rapids. sql.format.avr o.read.enabled	When set to true enables avro input acceleration	false	Runtime
spark.rapids .sql.format.av ro.reader.type	Sets the Avro reader type. We support different types that are optimized for different environments. The original Spark style reader can be selected by setting this to PERFILE which individually reads and copies files to the GPU. Loading many small files individually has high overhead, and using either COALESCING or MULTITHREADED is recommended instead. The COALESCING reader is good when using a local file system where the executors are on the same nodes or close to the nodes the data is being read on. This reader coalesces all the files assigned to a task into a single host buffer before sending it down to the GPU. It copies blocks from a single file into a host buffer in separate threads in parallel, see spar k.rapids.sql.m ultiThreadedRe ad.numThreads. MULTITHREADED is good for cloud environments where you are reading from a blobstore that is totally separate and likely has a higher I/O read cost. Many times the cloud environments also get better throughput when you have multiple readers in parallel. This reader uses multiple threads to read each file in parallel and each file is sent to the GPU separately. This allows the CPU to keep reading while GPU is also doing work. See spa rk.rapids.sql. multiThreadedR ead.numThreads and spark.rapi ds.sql.format. avro.multiThre adedRead.maxNu mFilesParallel to control the number of threads and amount of memory used. By default this is set to AUTO so we select the reader we think is best. This will either be the COALESCING or the MULTITHREADED based on whether we think the file is in the cloud. See spark.rapids .cloudSchemes.	AUTO	Runtime
spark.r apids.sql.form at.csv.enabled	When set to false disables all csv input and output acceleration. (only input is currently supported anyways)	true	Runtime
spark.rapids .sql.format.cs v.read.enabled	When set to false disables csv input acceleration	true	Runtime
s park.rapids.sq l.format.delta .write.enabled	When set to false disables Delta Lake output acceleration.	true	Runtime
spark.rapids. sql.format.hiv e.text.enabled	When set to false disables Hive text table acceleration	true	Runtime
spark.rapids .sql.format.hi ve.text.read.d ecimal.enabled	Hive text file reading is not 100% compatible when reading decimals. Hive has more limitations on what is valid compared to the GPU implementation in some corner cases. See https:// github.com/NVI DIA/spark-rapi ds/issues/7246	true	Runtime
spark.rapid s.sql.format.h ive.text.read. double.enabled	Hive text file reading is not 100% compatible when reading doubles.	true	Runtime
spar k.rapids.sql.f ormat.hive.tex t.read.enabled	When set to false disables Hive text table read acceleration	true	Runtime
spark.rapi ds.sql.format. hive.text.read .float.enabled	Hive text file reading is not 100% compatible when reading floats.	true	Runtime
spark .rapids.sql.fo rmat.hive.text .write.enabled	When set to false disables Hive text table write acceleration	false	Runtime
spark.rapid s.sql.format.i ceberg.enabled	When set to false disables all Iceberg acceleration	true	Runtime
sp ark.rapids.sql .format.iceber g.read.enabled	When set to false disables Iceberg input acceleration	true	Runtime
spark.ra pids.sql.forma t.json.enabled	When set to true enables all json input and output acceleration. (only input is currently supported anyways)	false	Runtime
spark.rapids. sql.format.jso n.read.enabled	When set to true enables json input acceleration	false	Runtime
spark.r apids.sql.form at.orc.enabled	When set to false disables all orc input and output acceleration	true	Runtime
spark.rapid s.sql.format.o rc.floatTypesT oString.enable	When reading an ORC file, the source data s chemas(schemas of ORC file) may differ from the target schemas (schemas of the reader), we need to handle the castings from source type to target type. Since float/double numbers in GPU have different precision with CPU, when casting float/double to string, the result of GPU is different from result of CPU spark. Its default value is true (this means the strings result will differ from result of CPU). If it’s set false explicitly and there exists casting from float/double to string in the job, then such behavior will cause an exception, and the job will fail.	true	Runtime
spark.rap ids.sql.format .orc.multiThre adedRead.maxNu mFilesParallel	A limit on the maximum number of files per task processed in parallel on the CPU side before the file is sent to the GPU. This affects the amount of host memory used when reading the files in parallel. Used with MULTITHREADED reader, see spark.rapids .sql.format.or c.reader.type.	2147483647	Runtime
spark.rapids.s ql.format.orc. multiThreadedR ead.numThreads	The maximum number of threads, on the executor, to use for reading small ORC files in parallel. This can not be changed at runtime after the executor has started. Used with MULTITHREADED reader, see spark.rapids .sql.format.or c.reader.type. DEPRECATED: use spa rk.rapids.sql. multiThreadedR ead.numThreads	None	Startup
spark.rapids .sql.format.or c.read.enabled	When set to false disables orc input acceleration	true	Runtime
spark.rapid s.sql.format.o rc.reader.type	Sets the ORC reader type. We support different types that are optimized for different environments. The original Spark style reader can be selected by setting this to PERFILE which individually reads and copies files to the GPU. Loading many small files individually has high overhead, and using either COALESCING or MULTITHREADED is recommended instead. The COALESCING reader is good when using a local file system where the executors are on the same nodes or close to the nodes the data is being read on. This reader coalesces all the files assigned to a task into a single host buffer before sending it down to the GPU. It copies blocks from a single file into a host buffer in separate threads in parallel, see spar k.rapids.sql.m ultiThreadedRe ad.numThreads. MULTITHREADED is good for cloud environments where you are reading from a blobstore that is totally separate and likely has a higher I/O read cost. Many times the cloud environments also get better throughput when you have multiple readers in parallel. This reader uses multiple threads to read each file in parallel and each file is sent to the GPU separately. This allows the CPU to keep reading while GPU is also doing work. See spa rk.rapids.sql. multiThreadedR ead.numThreads and spark.rap ids.sql.format .orc.multiThre adedRead.maxNu mFilesParallel to control the number of threads and amount of memory used. By default this is set to AUTO so we select the reader we think is best. This will either be the COALESCING or the MULTITHREADED based on whether we think the file is in the cloud. See spark.rapids .cloudSchemes.	AUTO	Runtime
spark.rapids. sql.format.orc .write.enabled	When set to false disables orc output acceleration	true	Runtime
spark.rapid s.sql.format.p arquet.enabled	When set to false disables all parquet input and output acceleration	true	Runtime
spark.rapids. sql.format.par quet.multiThre adedRead.maxNu mFilesParallel	A limit on the maximum number of files per task processed in parallel on the CPU side before the file is sent to the GPU. This affects the amount of host memory used when reading the files in parallel. Used with MULTITHREADED reader, see sp ark.rapids.sql .format.parque t.reader.type.	2147483647	Runtime
spar k.rapids.sql.f ormat.parquet. multiThreadedR ead.numThreads	The maximum number of threads, on the executor, to use for reading small Parquet files in parallel. This can not be changed at runtime after the executor has started. Used with COALESCING and MULTITHREADED reader, see sp ark.rapids.sql .format.parque t.reader.type. DEPRECATED: use spa rk.rapids.sql. multiThreadedR ead.numThreads	None	Startup
spark.r apids.sql.form at.parquet.mul tithreaded.com bine.sizeBytes	The target size in bytes to combine multiple small files together when using the MULTITHREADED parquet reader. With combine disabled, the MULTITHREADED reader reads the files in parallel and sends individual files down to the GPU, but that can be inefficient for small files. When combine is enabled, files that are ready within spark. rapids.sql.for mat.parquet.mu ltithreaded.co mbine.waitTime together, up to this threshold size, are combined before sending down to GPU. This can be disabled by setting it to 0. Note that combine also will not go over the spark.rap ids.sql.reader .batchSizeRows or spark.rapi ds.sql.reader. batchSizeBytes limits.	67108864	Runtime
spark. rapids.sql.for mat.parquet.mu ltithreaded.co mbine.waitTime	When using the multithreaded parquet reader with combine mode, how long to wait, in milliseconds, for more files to finish if haven’t met the size threshold. Note that this will wait this amount of time from when the last file was available, so total wait time could be larger then this.	200	Runtime
spar k.rapids.sql.f ormat.parquet. multithreaded. read.keepOrder	When using the MULTITHREADED reader, if this is set to true we read the files in the same order Spark does, otherwise the order may not be the same.	true	Runtime
sp ark.rapids.sql .format.parque t.read.enabled	When set to false disables parquet input acceleration	true	Runtime
spark.ra pids.sql.forma t.parquet.read er.footer.type	In some cases reading the footer of the file is very expensive. Typically this happens when there are a large number of columns and relatively few of them are being read on a large number of files. This provides the ability to use a different path to parse and filter the footer. AUTO is the default and decides which path to take using a heuristic. JAVA follows closely with what Apache Spark does. NATIVE will parse and filter the footer using C++.	AUTO	Runtime
s park.rapids.sq l.format.parqu et.reader.type	Sets the Parquet reader type. We support different types that are optimized for different environments. The original Spark style reader can be selected by setting this to PERFILE which individually reads and copies files to the GPU. Loading many small files individually has high overhead, and using either COALESCING or MULTITHREADED is recommended instead. The COALESCING reader is good when using a local file system where the executors are on the same nodes or close to the nodes the data is being read on. This reader coalesces all the files assigned to a task into a single host buffer before sending it down to the GPU. It copies blocks from a single file into a host buffer in separate threads in parallel, see spar k.rapids.sql.m ultiThreadedRe ad.numThreads. MULTITHREADED is good for cloud environments where you are reading from a blobstore that is totally separate and likely has a higher I/O read cost. Many times the cloud environments also get better throughput when you have multiple readers in parallel. This reader uses multiple threads to read each file in parallel and each file is sent to the GPU separately. This allows the CPU to keep reading while GPU is also doing work. See spa rk.rapids.sql. multiThreadedR ead.numThreads and spark.rapids. sql.format.par quet.multiThre adedRead.maxNu mFilesParallel to control the number of threads and amount of memory used. By default this is set to AUTO so we select the reader we think is best. This will either be the COALESCING or the MULTITHREADED based on whether we think the file is in the cloud. See spark.rapids .cloudSchemes.	AUTO	Runtime
spa rk.rapids.sql. format.parquet .write.enabled	When set to false disables parquet output acceleration	true	Runtime
spark.rapi ds.sql.format. parquet.writer .int96.enabled	When set to false, disables accelerated parquet write if the spark.sql .parquet.outpu tTimestampType is set to INT96	true	Runtime
spark.rapi ds.sql.hasExte ndedYearValues	Spark 3.2.0+ extended parsing of years in dates and timestamps to support the full range of possible values. Prior to this it was limited to a positive 4 digit year. The Accelerator does not support the extended range yet. This config indicates if your data includes this extended range or not, or if you don’t care about getting the correct values on values with the extended range.	true	Runtime
spark.rapids. sql.hashOptimi zeSort.enabled	Whether sorts should be inserted after some hashed operations to improve output ordering. This can improve output file sizes when saving to columnar formats.	false	Runtime
spark.rapids. sql.improvedFl oatOps.enabled	For some floating point operations spark uses one way to compute the value and the underlying cudf implementation can use an improved algorithm. In some cases this can result in cudf producing an answer when spark overflows.	true	Runtime
spark.rapids .sql.improvedT imeOps.enabled	When set to true, some operators will avoid overflowing by converting epoch days directly to seconds without first converting to microseconds	false	Runtime
spark. rapids.sql.inc ompatibleDateF ormats.enabled	When parsing strings as dates and timestamps in functions like u nix_timestamp, some formats are fully supported on the GPU and some are unsupported and will fall back to the CPU. Some formats behave differently on the GPU than the CPU. Spark on the CPU interprets date formats with unsupported trailing characters as nulls, while Spark on the GPU will parse the date with invalid trailing characters. More detail can be found at parsing strings as dates or times tamps.	false	Runtime
spark.rapids .sql.incompati bleOps.enabled	For operations that work, but are not 100% compatible with the Spark equivalent set if they should be enabled by default or disabled by default.	true	Runtime
spark.r apids.sql.join .cross.enabled	When set to true cross joins are enabled on the GPU	true	Runtime
spark.rapid s.sql.join.exi stence.enabled	When set to true existence joins are enabled on the GPU	true	Runtime
spark.rapid s.sql.join.ful lOuter.enabled	When set to true full outer joins are enabled on the GPU	true	Runtime
spark.r apids.sql.join .inner.enabled	When set to true inner joins are enabled on the GPU	true	Runtime
spark.rapi ds.sql.join.le ftAnti.enabled	When set to true left anti joins are enabled on the GPU	true	Runtime
spark.rapid s.sql.join.lef tOuter.enabled	When set to true left outer joins are enabled on the GPU	true	Runtime
spark.rapi ds.sql.join.le ftSemi.enabled	When set to true left semi joins are enabled on the GPU	true	Runtime
spark.rapids .sql.join.righ tOuter.enabled	When set to true right outer joins are enabled on the GPU	true	Runtime
spark.rapids.s ql.json.read.d ecimal.enabled	JSON reading is not 100% compatible when reading decimals.	false	Runtime
spark.rapids. sql.json.read. double.enabled	JSON reading is not 100% compatible when reading doubles.	true	Runtime
spark.rapids .sql.json.read .float.enabled	JSON reading is not 100% compatible when reading floats.	true	Runtime
sp ark.rapids.sql .metrics.level	GPU plans can produce a lot more metrics than CPU plans do. In very large queries this can sometimes result in going over the max result size limit for the driver. Supported values include DEBUG which will enable all metrics supported and typically only needs to be enabled when debugging the plugin. MODERATE which should output enough metrics to understand how long each part of the query is taking and how much data is going to each part of the query. ESSENTIAL which disables most metrics except those Apache Spark CPU plans will also report or their equivalents.	MODERATE	Runtime
spark.r apids.sql.mode	Set the mode for the Rapids Accelerator. The supported modes are explainOnly and executeOnGPU. This config can not be changed at runtime, you must restart the application for it to take affect. The default mode is executeOnGPU, which means the RAPIDS Accelerator plugin convert the Spark operations and execute them on the GPU when possible. The explainOnly mode allows running queries on the CPU and the RAPIDS Accelerator will evaluate the queries as if it was going to run on the GPU. The explanations of what would have run on the GPU and why are output in log messages. When using explainOnly mode, the default explain output is ALL, this can be changed by setting spark.rapid s.sql.explain. See that config for more details.	executeongpu	Startup
spa rk.rapids.sql. multiThreadedR ead.numThreads	The maximum number of threads on each executor to use for reading small files in parallel. This can not be changed at runtime after the executor has started. Used with COALESCING and MULTITHREADED readers, see sp ark.rapids.sql .format.parque t.reader.type, spark.rapids .sql.format.or c.reader.type, or spark.rapids .sql.format.av ro.reader.type for a discussion of reader types. If it is not set explicitly and spark. executor.cores is set, it will be tried to assign value of max(MULTIT HREAD_READ_NUM _THREADS_DEFAU LT, spark.exec utor.cores), where MULTITHR EAD_READ_NUM_T HREADS_DEFAULT = 20.	20	Startup
spark.r apids.sql.pyth on.gpu.enabled	This is an experimental feature and is likely to change in the future. Enable (true) or disable (false) support for scheduling Python Pandas UDFs with GPU resources. When enabled, pandas UDFs are assumed to share the same GPU that the RAPIDs accelerator uses and will honor the python GPU configs	false	Runtime
spark.rapi ds.sql.reader. batchSizeBytes	Soft limit on the maximum number of bytes the reader reads per batch. The readers will read chunks of data until this limit is met or exceeded. Note that the reader may estimate the number of bytes that will be used on the GPU in some cases based on the schema and number of rows in each batch.	2147483647	Runtime
spark.rap ids.sql.reader .batchSizeRows	Soft limit on the maximum number of rows the reader will read per batch. The orc and parquet readers will read row groups until this limit is met or exceeded. The limit is respected by the csv reader.	2147483647	Runtime
spa rk.rapids.sql. reader.chunked	Enable a chunked reader where possible. A chunked reader allows reading highly compressed data that could not be read otherwise, but at the expense of more GPU memory, and in some cases more GPU computation.	true	Runtime
spa rk.rapids.sql. regexp.enabled	Specifies whether supported regular expressions will be evaluated on the GPU. Unsupported expressions will fall back to CPU. However, there are some known edge cases that will still execute on GPU and produce incorrect results and these are documented in the compatibility guide. Setting this config to false will make all regular expressions run on the CPU instead.	true	Runtime
s park.rapids.sq l.regexp.maxSt ateMemoryBytes	Specifies the maximum memory on GPU to be used for regular e xpressions.The memory usage is an estimate based on an upper-bound approximation on the complexity of the regular expression. Note that the actual memory usage may still be higher than this estimate depending on the number of rows in the datacolumn and the input strings themselves. It is recommended to not set this to more than 3 times spa rk.rapids.sql. batchSizeBytes	2147483647	Runtime
spa rk.rapids.sql. replaceSortMer geJoin.enabled	Allow replacing sortMergeJoin with HashJoin	true	Runtime
spark.ra pids.sql.rowBa sedUDF.enabled	When set to true, optimizes a row-based UDF in a GPU operation by transferring only the data it needs between GPU and CPU inside a query operation, instead of falling this operation back to CPU. This is an experimental feature, and this config might be removed in the future.	false	Runtime
spark.rap ids.sql.shuffl e.spillThreads	Number of threads used to spill shuffle data to disk in the background.	6	Runtime
spark.r apids.sql.stab leSort.enabled	Enable or disable stable sorting. Apache Spark’s sorting is typically a stable sort, but sort stability cannot be guaranteed in distributed work loads because the order in which upstream data arrives to a task is not guaranteed. Sort stability then only matters when reading and sorting data from a file using a single t ask/partition. Because of limitations in the plugin when you enable stable sorting all of the data for a single task will be combined into a single batch before sorting. This currently disables spilling from GPU memory if the data size is too large.	false	Runtime
spark.rapids .sql.suppressP lanningFailure	Option to fallback an individual query to CPU if an unexpected condition prevents the query plan from being converted to a GPU-enabled one. Note this is different from a normal CPU fallback for a yet-t o-be-supported Spark SQL feature. If this happens the error should be reported and investigated as a GitHub issue.	false	Runtime
spark.ra pids.sql.udfCo mpiler.enabled	When set to true, Scala UDFs will be considered for compilation as Catalyst expressions	false	Runtime
spark.rapids. sql.variableFl oatAgg.enabled	Spark assumes that all operations produce the exact same result each time. This is not true for some floating point aggregations, which can produce slightly different results on the GPU as the aggregation is done in parallel. This can enable those operations if you know the query is only computing it once.	true	Runtime
spark.rapids.s ql.window.rang e.byte.enabled	When the order-by column of a range based window is byte type and the range boundary calculated for a value has overflow, CPU and GPU will get the different results. When set to false disables the range window acceleration for the byte type order-by column	false	Runtime
spa rk.rapids.sql. window.range.d ecimal.enabled	When set to false, this disables the range window acceleration for the DECIMAL type order-by column	true	Runtime
spark.rapids. sql.window.ran ge.int.enabled	When the order-by column of a range based window is int type and the range boundary calculated for a value has overflow, CPU and GPU will get the different results. When set to false disables the range window acceleration for the int type order-by column	true	Runtime
spark.rapids.s ql.window.rang e.long.enabled	When the order-by column of a range based window is long type and the range boundary calculated for a value has overflow, CPU and GPU will get the different results. When set to false disables the range window acceleration for the long type order-by column	true	Runtime
s park.rapids.sq l.window.range .short.enabled	When the order-by column of a range based window is short type and the range boundary calculated for a value has overflow, CPU and GPU will get the different results. When set to false disables the range window acceleration for the short type order-by column	false	Runtime

Supported GPU Operators and Fine Tuning

The RAPIDS Accelerator for Apache Spark can be configured to enable or disable specific GPU accelerated expressions. Enabled expressions are candidates for GPU execution. If the expression is configured as disabled, the accelerator plugin will not attempt replacement, and it will run on the CPU.

Please leverage the spark.rapids.sql.explain setting to get feedback from the plugin as to why parts of a query may not be executing on the GPU.

Note

Setting spark.rapids.sql.incompatibleOps.enabled=true will enable all the settings in the table below which are not enabled by default due to incompatibilities.

Expressions

Name	SQL Function(s)	Description	Default Value	Notes
spark.rap ids.sql.exp ression.Abs	abs	Absolute value	true	None
spark.rapi ds.sql.expr ession.Acos	acos	Inverse cosine	true	None
spark.rapid s.sql.expre ssion.Acosh	acosh	Inverse hyperbolic cosine	true	None
spark.rap ids.sql.exp ression.Add	+	Addition	true	None
spark.rapid s.sql.expre ssion.Alias		Gives a column a name	true	None
spark.rap ids.sql.exp ression.And	and	Logical AND	true	None
spa rk.rapids.s ql.expressi on.AnsiCast		Convert a column of one type of data into another type	true	None
spark.ra pids.sql.ex pression.Ar rayContains	array _contains	Returns a boolean if the array contains the passed in key	true	None
spark. rapids.sql. expression. ArrayExcept	arr ay_except	Returns an array of the elements in array1 but not in array2, without duplicates	true	This is not 100% compatible with the Spark version because the GPU imp lementation treats -0.0 and 0.0 as equal, but the CPU imp lementation currently does not (see SP ARK-39845). Also, Apache Spark 3.1.3 fixed issue SPARK-36741 where NaNs in these set like operators were not treated as being equal. We have chosen to break with co mpatibility for the older versions of Spark in this instance and handle NaNs the same as 3.1.3+
spark. rapids.sql. expression. ArrayExists	exists	Return true if any element satisfies the predicate Lam bdaFunction	true	None
spark.rap ids.sql.exp ression.Arr ayIntersect	array_ intersect	Returns an array of the elements in the i ntersection of array1 and array2, without duplicates	true	This is not 100% compatible with the Spark version because the GPU imp lementation treats -0.0 and 0.0 as equal, but the CPU imp lementation currently does not (see SP ARK-39845). Also, Apache Spark 3.1.3 fixed issue SPARK-36741 where NaNs in these set like operators were not treated as being equal. We have chosen to break with co mpatibility for the older versions of Spark in this instance and handle NaNs the same as 3.1.3+
spa rk.rapids.s ql.expressi on.ArrayMax	`` array_max``	Returns the maximum value in the array	true	None
spa rk.rapids.s ql.expressi on.ArrayMin	`` array_min``	Returns the minimum value in the array	true	None
spark. rapids.sql. expression. ArrayRemove	arr ay_remove	Returns the array after removing all elements that equal to the input element (right) from the input array (left)	true	None
spark. rapids.sql. expression. ArrayRepeat	arr ay_repeat	Returns the array containing the given input value (left) count (right) times	true	None
spark.rap ids.sql.exp ression.Arr ayTransform	`` transform``	Transform elements in an array using the transform function. This is similar to a map in functional programming	true	None
spark .rapids.sql .expression .ArrayUnion	ar ray_union	Returns an array of the elements in the union of array1 and array2, without duplicates.	true	This is not 100% compatible with the Spark version because the GPU imp lementation treats -0.0 and 0.0 as equal, but the CPU imp lementation currently does not (see SP ARK-39845). Also, Apache Spark 3.1.3 fixed issue SPARK-36741 where NaNs in these set like operators were not treated as being equal. We have chosen to break with co mpatibility for the older versions of Spark in this instance and handle NaNs the same as 3.1.3+
spark.ra pids.sql.ex pression.Ar raysOverlap	array s_overlap	Returns true if a1 contains at least a non-null element present also in a2. If the arrays have no common element and they are both non-empty and either of them contains a null element null is returned, false otherwise.	true	This is not 100% compatible with the Spark version because the GPU imp lementation treats -0.0 and 0.0 as equal, but the CPU imp lementation currently does not (see SP ARK-39845). Also, Apache Spark 3.1.3 fixed issue SPARK-36741 where NaNs in these set like operators were not treated as being equal. We have chosen to break with co mpatibility for the older versions of Spark in this instance and handle NaNs the same as 3.1.3+
spar k.rapids.sq l.expressio n.ArraysZip	a rrays_zip	Returns a merged array of structs in which the N-th struct contains all N-th values of input arrays.	true	None
spark.rapi ds.sql.expr ession.Asin	asin	Inverse sine	true	None
spark.rapid s.sql.expre ssion.Asinh	asinh	Inverse hyperbolic sine	true	None
spark.rapid s.sql.expre ssion.AtLea stNNonNulls		Checks if number of non null/Nan values is greater than a given value	true	None
spark.rapi ds.sql.expr ession.Atan	atan	Inverse tangent	true	None
spark.rapid s.sql.expre ssion.Atanh	atanh	Inverse hyperbolic tangent	true	None
sp ark.rapids. sql.express ion.Attribu teReference		References an input column	true	None
s park.rapids .sql.expres sion.BRound	bround	Round an expression to d decimal places using HALF_EVEN rounding mode	true	None
spar k.rapids.sq l.expressio n.BitLength	b it_length	The bit length of string data	true	None
spark .rapids.sql .expression .BitwiseAnd	&	Returns the bitwise AND of the operands	true	None
spark .rapids.sql .expression .BitwiseNot	~	Returns the bitwise NOT of the operands	true	None
spar k.rapids.sq l.expressio n.BitwiseOr	\|	Returns the bitwise OR of the operands	true	None
spark .rapids.sql .expression .BitwiseXor	^	Returns the bitwise XOR of the operands	true	None
spa rk.rapids.s ql.expressi on.CaseWhen	when	CASE WHEN expression	true	None
spark.rapi ds.sql.expr ession.Cast	t imestamp, ` tinyint`, binary, float, `` smallint``, string, ` decimal`, double, ` boolean`, cast, date, int, bigint	Convert a column of one type of data into another type	true	None
spark.rapi ds.sql.expr ession.Cbrt	cbrt	Cube root	true	None
spark.rapi ds.sql.expr ession.Ceil	` ceiling`, ceil	Ceiling of a number	true	None
spark.ra pids.sql.ex pression.Ch eckOverflow		Ch eckOverflow after arithmetic operations between DecimalType data	true	None
spa rk.rapids.s ql.expressi on.Coalesce	` coalesce`	Returns the first non-null argument if exists. Otherwise, null	true	None
s park.rapids .sql.expres sion.Concat	concat	List/String concatenate	true	None
spa rk.rapids.s ql.expressi on.ConcatWs	`` concat_ws``	C oncatenates multiple input strings or array of strings into a single string using a given separator	true	None
spa rk.rapids.s ql.expressi on.Contains		Contains	true	None
spark.rap ids.sql.exp ression.Cos	cos	Cosine	true	None
spark.rapi ds.sql.expr ession.Cosh	cosh	Hyperbolic cosine	true	None
spark.rap ids.sql.exp ression.Cot	cot	Cotangent	true	None
spark. rapids.sql. expression. CreateArray	array	Returns an array with the given elements	true	None
spar k.rapids.sq l.expressio n.CreateMap	map	Create a map	true	None
s park.rapids .sql.expres sion.Create NamedStruct	name d_struct, struct	Creates a struct with the given field names and values	true	None
spark. rapids.sql. expression. CurrentRow$		Special boundary for a window frame, indicating stopping at the current row	true	None
sp ark.rapids. sql.express ion.DateAdd	` date_add`	Returns the date that is num_days after start_date	true	None
spark.rapi ds.sql.expr ession.Date AddInterval		Adds interval to date	true	None
spa rk.rapids.s ql.expressi on.DateDiff	` datediff`	Returns the number of days from startDate to endDate	true	None
spark.rapi ds.sql.expr ession.Date FormatClass	da te_format	Converts timestamp to a value of string in the format specified by the date format	true	None
sp ark.rapids. sql.express ion.DateSub	` date_sub`	Returns the date that is num_days before start_date	true	None
spark .rapids.sql .expression .DayOfMonth	da yofmonth, day	Returns the day of the month from a date or timestamp	true	None
spar k.rapids.sq l.expressio n.DayOfWeek	`` dayofweek``	Returns the day of the week (1 = Sunday… 7=Saturday)	true	None
spar k.rapids.sq l.expressio n.DayOfYear	`` dayofyear``	Returns the day of the year from a date or timestamp	true	None
spar k.rapids.sq l.expressio n.DenseRank	d ense_rank	Window function that returns the dense rank value within the aggregation window	true	None
s park.rapids .sql.expres sion.Divide	/	Division	true	None
spar k.rapids.sq l.expressio n.ElementAt	e lement_at	Returns element of array at giv en(1-based) index in value if column is array. Returns value for the given key in value if column is map.	true	None
spa rk.rapids.s ql.expressi on.EndsWith		Ends with	true	None
spark.ra pids.sql.ex pression.Eq ualNullSafe	<=>	Check if the values are equal including nulls <=>	true	None
sp ark.rapids. sql.express ion.EqualTo	=, ==	Check if the values are equal	true	None
spark.rap ids.sql.exp ression.Exp	exp	Euler’s number e raised to a power	true	None
sp ark.rapids. sql.express ion.Explode	` explode`, expl ode_outer	Given an input array produces a sequence of rows for each value in the array	true	None
spark.rapid s.sql.expre ssion.Expm1	expm1	Euler’s number e raised to a power minus 1	true	None
spark.rapid s.sql.expre ssion.Floor	floor	Floor of a number	true	None
spark.rapid s.sql.expre ssion.FromU TCTimestamp	from_utc_ timestamp	Render the input UTC timestamp in the input timezone	true	None
spark.r apids.sql.e xpression.F romUnixTime	from _unixtime	Get the string from a unix timestamp	true	None
spark.r apids.sql.e xpression.G etArrayItem		Gets the field at ordinal in the Array	true	None
spar k.rapids.sq l.expressio n.GetArrayS tructFields		Extracts the o rdinal-th fields of all array elements for the data with the type of array of struct	true	None
spark.ra pids.sql.ex pression.Ge tJsonObject	get_js on_object	Extracts a json object from path	true	None
spark. rapids.sql. expression. GetMapValue		Gets Value from a Map based on a key	true	None
spark.rap ids.sql.exp ression.Get StructField		Gets the named field of the struct	true	None
spark.r apids.sql.e xpression.G etTimestamp		Gets timestamps from strings using given pattern.	true	None
spark. rapids.sql. expression. GreaterThan	>	> operator	true	None
sp ark.rapids. sql.express ion.Greater ThanOrEqual	>=	>= operator	true	None
spa rk.rapids.s ql.expressi on.Greatest	` greatest`	Returns the greatest value of all parameters, skipping null values	true	None
spark.rapi ds.sql.expr ession.Hour	hour	Returns the hour component of the strin g/timestamp	true	None
spark.rapid s.sql.expre ssion.Hypot	hypot	Pythagorean addition ( Hypotenuse) of real numbers	true	None
spark.ra pids.sql.ex pression.If	if	IF expression	true	None
spark.ra pids.sql.ex pression.In	in	IN operator	true	None
spark.rapid s.sql.expre ssion.InSet		INSET operator	true	None
sp ark.rapids. sql.express ion.InitCap	initcap	Returns str with the first letter of each word in uppercase. All other letters are in lowercase	true	This is not 100% compatible with the Spark version because the Unicode version used by cuDF and the JVM may differ, resulting in some corner-case characters not changing case correctly.
spar k.rapids.sq l.expressio n.InputFile BlockLength	inp ut_file_blo ck_length	Returns the length of the block being read, or -1 if not available	true	None
spa rk.rapids.s ql.expressi on.InputFil eBlockStart	in put_file_bl ock_start	Returns the start offset of the block being read, or -1 if not available	true	None
spark.ra pids.sql.ex pression.In putFileName	input_ file_name	Returns the name of the file being read, or empty string if not available	true	None
spark.rap ids.sql.exp ression.Int egralDivide	div	Division with a integer result	true	None
spark.rapid s.sql.expre ssion.IsNaN	isnan	Checks if a value is NaN	true	None
spar k.rapids.sq l.expressio n.IsNotNull	`` isnotnull``	Checks if a value is not null	true	None
s park.rapids .sql.expres sion.IsNull	isnull	Checks if a value is null	true	None
spark.ra pids.sql.ex pression.Js onToStructs	`` from_json``	Returns a struct value with the given jsonStr and schema	false	This is disabled by default because parsing JSON from a column has a large number of issues and should be considered beta quality right now.
spar k.rapids.sq l.expressio n.JsonTuple	j son_tuple	Returns a tuple like the function get_j son_object, but it takes multiple names. All the input parameters and output column types are string.	true	None
s park.rapids .sql.expres sion.KnownF loatingPoin tNormalized		Tag to prevent redundant no rmalization	true	None
spark.r apids.sql.e xpression.K nownNotNull		Tag an expression as known to not be null	true	None
spark.rap ids.sql.exp ression.Lag	lag	Window function that returns N entries behind this one	true	None
spark.rap ids.sql.exp ression.Lam bdaFunction		Holds a higher order SQL function	true	None
sp ark.rapids. sql.express ion.LastDay	` last_day`	Returns the last day of the month which the date belongs to	true	None
spark.rapi ds.sql.expr ession.Lead	lead	Window function that returns N entries ahead of this one	true	None
spark.rapid s.sql.expre ssion.Least	least	Returns the least value of all parameters, skipping null values	true	None
s park.rapids .sql.expres sion.Length	length, characte r_length, ch ar_length	String character length or binary byte length	true	None
spa rk.rapids.s ql.expressi on.LessThan	<	< operator	true	None
spark.rapi ds.sql.expr ession.Less ThanOrEqual	<=	<= operator	true	None
spark.rapi ds.sql.expr ession.Like	like	Like	true	None
sp ark.rapids. sql.express ion.Literal		Holds a static value from the query	true	None
spark.rap ids.sql.exp ression.Log	ln	Natural log	true	None
spark.rapid s.sql.expre ssion.Log10	log10	Log base 10	true	None
spark.rapid s.sql.expre ssion.Log1p	log1p	Natural log 1 + expr	true	None
spark.rapi ds.sql.expr ession.Log2	log2	Log base 2	true	None
spar k.rapids.sq l.expressio n.Logarithm	log	Log variable base	true	None
spark.rapid s.sql.expre ssion.Lower	lower, lcase	String lowercase operator	true	This is not 100% compatible with the Spark version because the Unicode version used by cuDF and the JVM may differ, resulting in some corner-case characters not changing case correctly.
spark. rapids.sql. expression. MakeDecimal		Create a Decimal from an unscaled long value for some aggregation op timizations	true	None
spar k.rapids.sq l.expressio n.MapConcat	m ap_concat	Returns the union of all the given maps	true	None
spark .rapids.sql .expression .MapEntries	ma p_entries	Returns an unordered array of all entries in the given map	true	None
spar k.rapids.sq l.expressio n.MapFilter	m ap_filter	Filters entries in a map using the function	true	None
sp ark.rapids. sql.express ion.MapKeys	` map_keys`	Returns an unordered array containing the keys of the map	true	None
spar k.rapids.sq l.expressio n.MapValues	m ap_values	Returns an unordered array containing the values of the map	true	None
spark.rap ids.sql.exp ression.Md5	md5	MD5 hash operator	true	None
s park.rapids .sql.expres sion.Minute	minute	Returns the minute component of the strin g/timestamp	true	None
spark.rap ids.sql.exp ression.Mon otonicallyI ncreasingID	monoton ically_incr easing_id	Returns mo notonically increasing 64-bit integers	true	None
spark.rapid s.sql.expre ssion.Month	month	Returns the month from a date or timestamp	true	None
spa rk.rapids.s ql.expressi on.Multiply	*	Mul tiplication	true	None
spark. rapids.sql. expression. Murmur3Hash	hash	Murmur3 hash operator	true	None
spark.rapid s.sql.expre ssion.NaNvl	nanvl	Evaluates to left iff left is not NaN, right otherwise	true	None
spa rk.rapids.s ql.expressi on.NamedLam bdaVariable		A parameter to a higher order SQL function	true	None
spark.rap ids.sql.exp ression.Not	!, not	Boolean not operator	true	None
spa rk.rapids.s ql.expressi on.NthValue	`` nth_value``	nth window operator	true	None
spark. rapids.sql. expression. OctetLength	oct et_length	The byte length of string data	true	None
spark.ra pids.sql.ex pression.Or	or	Logical OR	true	None
spark. rapids.sql. expression. PercentRank	per cent_rank	Window function that returns the percent rank value within the aggregation window	true	None
spark.rapi ds.sql.expr ession.Pmod	pmod	Pmod	true	None
spark .rapids.sql .expression .PosExplode	posexplo de_outer, p osexplode	Given an input array produces a sequence of rows for each value in the array	true	None
spark.rap ids.sql.exp ression.Pow	pow, power	lhs ^ rhs	true	None
spark.rapi ds.sql.expr ession.Prec iseTimestam pConversion		Expression used internally to convert the Ti mestampType to Long and back without losing precision, i.e. in mi croseconds. Used in time windowing	true	None
spark.rapid s.sql.expre ssion.Promo tePrecision		Promo tePrecision before arithmetic operations between DecimalType data	true	None
spar k.rapids.sq l.expressio n.PythonUDF		UDF run in an external python process. Does not actually run on the GPU, but the transfer of data to/from it can be accelerated	true	None
sp ark.rapids. sql.express ion.Quarter	quarter	Returns the quarter of the year for date, in the range 1 to 4	true	None
spark.rapid s.sql.expre ssion.RLike	rlike	Regular expression version of Like	true	None
spark .rapids.sql .expression .RaiseError	ra ise_error	Throw an exception	true	None
spark.rapi ds.sql.expr ession.Rand	random, rand	Generate a random column with i.i.d. uniformly distributed values in [0, 1)	true	None
spark.rapi ds.sql.expr ession.Rank	rank	Window function that returns the rank value within the aggregation window	true	None
spark.ra pids.sql.ex pression.Re gExpExtract	regex p_extract	Extract a specific group identified by a regular expression	true	None
spark.rapid s.sql.expre ssion.RegEx pExtractAll	regexp_ex tract_all	Extract all strings matching a regular expression co rresponding to the regex group index	true	None
spark.ra pids.sql.ex pression.Re gExpReplace	regex p_replace	String replace using a regular expression pattern	true	None
spar k.rapids.sq l.expressio n.Remainder	%, mod	Remainder or modulo	true	None
spark.ra pids.sql.ex pression.Re plicateRows		Given an input row replicates the row N times	true	None
sp ark.rapids. sql.express ion.Reverse	reverse	Returns a reversed string or an array with reverse order of elements	true	None
spark.rapi ds.sql.expr ession.Rint	rint	Rounds up a double value to the nearest double equal to an integer	true	None
spark.rapid s.sql.expre ssion.Round	round	Round an expression to d decimal places using HALF_UP rounding mode	true	None
spar k.rapids.sq l.expressio n.RowNumber	r ow_number	Window function that returns the index for the row within the aggregation window	true	None
spa rk.rapids.s ql.expressi on.ScalaUDF		User Defined Function, the UDF can choose to implement a RAPIDS accelerated interface to get better p erformance.	true	None
s park.rapids .sql.expres sion.Second	second	Returns the second component of the strin g/timestamp	true	None
spa rk.rapids.s ql.expressi on.Sequence	` sequence`	Sequence	true	None
spar k.rapids.sq l.expressio n.ShiftLeft	`` shiftleft``	Bitwise shift left («)	true	None
spark .rapids.sql .expression .ShiftRight	s hiftright	Bitwise shift right (»)	true	None
sp ark.rapids. sql.express ion.ShiftRi ghtUnsigned	shiftrigh tunsigned	Bitwise unsigned shift right (»>)	true	None
s park.rapids .sql.expres sion.Signum	sign, signum	Returns -1.0, 0.0 or 1.0 as expr is negative, 0 or positive	true	None
spark.rap ids.sql.exp ression.Sin	sin	Sine	true	None
spark.rapi ds.sql.expr ession.Sinh	sinh	Hyperbolic sine	true	None
spark.rapi ds.sql.expr ession.Size	size, ca rdinality	The size of an array or a map	true	None
spar k.rapids.sq l.expressio n.SortArray	s ort_array	Returns a sorted array with the input array and the ascending / descending order	true	None
spar k.rapids.sq l.expressio n.SortOrder		Sort order	true	None
spark.rapid s.sql.expre ssion.Spark PartitionID	spark_par tition_id	Returns the current partition id	true	None
spar k.rapids.sq l.expressio n.Specified WindowFrame		Sp ecification of the width of the group (or “frame”) of input rows around which a window function is evaluated	true	None
spark.rapi ds.sql.expr ession.Sqrt	sqrt	Square root	true	None
spark .rapids.sql .expression .StartsWith		Starts with	true	None
spark. rapids.sql. expression. StringInstr	instr	Instr string operator	true	None
spark .rapids.sql .expression .StringLPad	lpad	Pad a string on the left	true	None
spark.r apids.sql.e xpression.S tringLocate	`` position``, locate	Substring search operator	true	None
spark .rapids.sql .expression .StringRPad	rpad	Pad a string on the right	true	None
spark.r apids.sql.e xpression.S tringRepeat	repeat	S tringRepeat operator that repeats the given strings with numbers of times given by repeatTimes	true	None
spark.ra pids.sql.ex pression.St ringReplace	replace	St ringReplace operator	true	None
spark. rapids.sql. expression. StringSplit	split	Splits str around occurrences that match regex	true	None
spark. rapids.sql. expression. StringToMap	s tr_to_map	Creates a map after splitting the input string into pairs of key-value strings	true	None
spark .rapids.sql .expression .StringTrim	trim	StringTrim operator	true	None
spark.rap ids.sql.exp ression.Str ingTrimLeft	ltrim	Str ingTrimLeft operator	true	None
spark.rapi ds.sql.expr ession.Stri ngTrimRight	rtrim	Stri ngTrimRight operator	true	None
spar k.rapids.sq l.expressio n.Substring	substr, `` substring``	Substring operator	true	None
spark.rap ids.sql.exp ression.Sub stringIndex	substr ing_index	subs tring_index operator	true	None
spa rk.rapids.s ql.expressi on.Subtract	-	Subtraction	true	None
spark.rap ids.sql.exp ression.Tan	tan	Tangent	true	None
spark.rapi ds.sql.expr ession.Tanh	tanh	Hyperbolic tangent	true	None
sp ark.rapids. sql.express ion.TimeAdd		Adds interval to timestamp	true	None
spar k.rapids.sq l.expressio n.ToDegrees	degrees	Converts radians to degrees	true	None
spar k.rapids.sq l.expressio n.ToRadians	radians	Converts degrees to radians	true	None
spark.rapi ds.sql.expr ession.ToUn ixTimestamp	to_unix_ timestamp	Returns the UNIX timestamp of the given time	true	None
spark.ra pids.sql.ex pression.Tr ansformKeys	trans form_keys	Transform keys in a map using a transform function	true	None
spark.rapi ds.sql.expr ession.Tran sformValues	transfo rm_values	Transform values in a map using a transform function	true	None
spark .rapids.sql .expression .UnaryMinus	` negative`	Negate a numeric value	true	None
spark.ra pids.sql.ex pression.Un aryPositive	` positive`	A numeric value with a + in front of it	true	None
spa rk.rapids.s ql.expressi on.Unbounde dFollowing$		Special boundary for a window frame, indicating all rows preceding the current row	true	None
spa rk.rapids.s ql.expressi on.Unbounde dPreceding$		Special boundary for a window frame, indicating all rows preceding the current row	true	None
spark.ra pids.sql.ex pression.Un ixTimestamp	unix_ timestamp	Returns the UNIX timestamp of current or specified time	true	None
spark.ra pids.sql.ex pression.Un scaledValue		Convert a Decimal to an unscaled long value for some aggregation op timizations	true	None
spark.rapid s.sql.expre ssion.Upper	upper, ucase	String uppercase operator	true	This is not 100% compatible with the Spark version because the Unicode version used by cuDF and the JVM may differ, resulting in some corner-case characters not changing case correctly.
sp ark.rapids. sql.express ion.WeekDay	weekday	Returns the day of the week (0 = Monda y…6=Sunday)	true	None
spark.rapid s.sql.expre ssion.Windo wExpression		Calculates a return value for every input row of a table based on a group (or “window”) of rows	true	None
spar k.rapids.sq l.expressio n.WindowSpe cDefinition		Sp ecification of a window function, indicating the pa rtitioning- expression, the row ordering, and the width of the window	true	None
spark.rapi ds.sql.expr ession.Year	year	Returns the year from a date or timestamp	true	None
spa rk.rapids.s ql.expressi on.Aggregat eExpression		Aggregate expression	true	None
spark .rapids.sql .expression .Approximat ePercentile	percentil e_approx, approx_p ercentile	Approximate percentile	true	This is not 100% compatible with the Spark version because the GPU imp lementation of approx _percentile is not bit-for-bit compatible with Apache Spark
sp ark.rapids. sql.express ion.Average	avg, mean	Average aggregate operator	true	None
spark. rapids.sql. expression. CollectList	col lect_list	Collect a list of non-unique elements, not supported in reduction	true	None
spark .rapids.sql .expression .CollectSet	co llect_set	Collect a set of unique elements, not supported in reduction	true	None
spark.rapid s.sql.expre ssion.Count	count	Count aggregate operator	true	None
spark.rapid s.sql.expre ssion.First	fir st_value, first	first aggregate operator	true	None
spark.rapi ds.sql.expr ession.Last	last, l ast_value	last aggregate operator	true	None
spark.rap ids.sql.exp ression.Max	max	Max aggregate operator	true	None
spark.rap ids.sql.exp ression.Min	min	Min aggregate operator	true	None
spark .rapids.sql .expression .PivotFirst		PivotFirst operator	true	None
spar k.rapids.sq l.expressio n.StddevPop	s tddev_pop	Aggregation computing population standard deviation	true	None
spark .rapids.sql .expression .StddevSamp	std dev_samp, std, stddev	Aggregation computing sample standard deviation	true	None
spark.rap ids.sql.exp ression.Sum	sum	Sum aggregate operator	true	None
spark. rapids.sql. expression. VariancePop	var_pop	Aggregation computing population variance	true	None
spark.r apids.sql.e xpression.V arianceSamp	`` var_samp``, ` variance`	Aggregation computing sample variance	true	None
spa rk.rapids.s ql.expressi on.Normaliz eNaNAndZero		Normalize NaN and zero	true	None
spark.rap ids.sql.exp ression.Sca larSubquery		Subquery that will return only one row and one column	true	None
spark.rap ids.sql.exp ression.Hiv eGenericUDF		Hive Generic UDF, the UDF can choose to implement a RAPIDS accelerated interface to get better performance	true	None
spark.ra pids.sql.ex pression.Hi veSimpleUDF		Hive UDF, the UDF can choose to implement a RAPIDS accelerated interface to get better performance	true	None

Execution

Name	Description	Default Value	Notes
spark. rapids.sql.exe c.CoalesceExec	The backend for the dataframe coalesce method	true	None
spark.rapi ds.sql.exec.Co llectLimitExec	Reduce to single partition and apply limit	false	This is disabled by default because Collect Limit replacement can be slower on the GPU, if huge number of rows in a batch it could help by limiting the number of rows transferred from GPU to CPU
spar k.rapids.sql.e xec.ExpandExec	The backend for the expand operator	true	None
spark.rapids .sql.exec.File SourceScanExec	Reading data from files, often from Hive tables	true	None
spar k.rapids.sql.e xec.FilterExec	The backend for most filter statements	true	None
spark. rapids.sql.exe c.GenerateExec	The backend for operations that generate more output rows than input rows like explode	true	None
spark.rap ids.sql.exec.G lobalLimitExec	Limiting of results across partitions	true	None
spark.ra pids.sql.exec. LocalLimitExec	Per-partition limiting of results	true	None
spark .rapids.sql.ex ec.ProjectExec	The backend for most select, withColumn and dropColumn statements	true	None
spa rk.rapids.sql. exec.RangeExec	The backend for range operator	true	None
spar k.rapids.sql.e xec.SampleExec	The backend for the sample operator	true	None
sp ark.rapids.sql .exec.SortExec	The backend for the sort operator	true	None
s park.rapids.sq l.exec.Subquer yBroadcastExec	Plan to collect and transform the broadcast key values	true	None
spark .rapids.sql.ex ec.TakeOrdered AndProjectExec	Take the first limit elements as defined by the sortOrder, and do projection if needed	true	None
spa rk.rapids.sql. exec.UnionExec	The backend for the union operator	true	None
spa rk.rapids.sql. exec.CustomShu ffleReaderExec	A wrapper of shuffle query stage	true	None
spark.rapid s.sql.exec.Has hAggregateExec	The backend for hash based aggregations	true	None
spa rk.rapids.sql. exec.ObjectHas hAggregateExec	The backend for hash based aggregations supporting TypedImper ativeAggregate functions	true	None
spark.rapid s.sql.exec.Sor tAggregateExec	The backend for sort based aggregations	true	None
s park.rapids.sq l.exec.InMemor yTableScanExec	Implementation of InMemor yTableScanExec to use GPU accelerated caching	true	None
sp ark.rapids.sql .exec.DataWrit ingCommandExec	Writing data	true	None
spark.rapids. sql.exec.Execu tedCommandExec	Eagerly executed commands	true	None
spark.r apids.sql.exec .BatchScanExec	The backend for most file input	true	None
s park.rapids.sq l.exec.Broadca stExchangeExec	The backend for broadcast exchange of data	true	None
spark.rapids. sql.exec.Shuff leExchangeExec	The backend for most data being exchanged between processes	true	None
s park.rapids.sq l.exec.Broadca stHashJoinExec	Implementation of join using broadcast data	true	None
spark.r apids.sql.exec .BroadcastNest edLoopJoinExec	Implementation of join using brute force. Full outer joins and joins where the broadcast side matches the join side (e.g.: LeftOuter with left broadcast) are not supported	true	None
spark.rapids.s ql.exec.Cartes ianProductExec	Implementation of join using brute force	true	None
spark.rapids.s ql.exec.Shuffl edHashJoinExec	Implementation of join using hashed shuffled data	true	None
spark.rapid s.sql.exec.Sor tMergeJoinExec	Sort merge join, replacing with shuffled hash join	true	None
s park.rapids.sq l.exec.Aggrega teInPandasExec	The backend for an Aggregation Pandas UDF, this accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled.	true	None
spark.rapids. sql.exec.Arrow EvalPythonExec	The backend of the Scalar Pandas UDFs. Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled	true	None
spark.r apids.sql.exec .FlatMapCoGrou psInPandasExec	The backend for CoGrouped Aggregation Pandas UDF. Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled.	false	This is disabled by default because Performance is not ideal with many small groups
spark .rapids.sql.ex ec.FlatMapGrou psInPandasExec	The backend for Flat Map Groups Pandas UDF, Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled.	true	None
spark.rap ids.sql.exec.M apInPandasExec	The backend for Map Pandas Iterator UDF. Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled.	true	None
spark.rapids .sql.exec.Wind owInPandasExec	The backend for Window Aggregation Pandas UDF, Accelerates the data transfer between the Java process and the Python process. It also supports scheduling GPU resources for the Python process when enabled. For now it only supports row based window frame.	false	This is disabled by default because it only supports row based frame for now
spar k.rapids.sql.e xec.WindowExec	W indow-operator backend	true	None
spark.rapid s.sql.exec.Hiv eTableScanExec	Scan Exec to read Hive delimited text tables	true	None

Commands

Name	Description	Default Value	Notes
spark.rapids .sql.command.SaveIn toDataSourceCommand	Write to a data source	true	None

Scans

Name	Description	Default Value	Notes
spark.rapids.sql.input.CSVScan	CSV parsing	true	None
spark.rapids.sql.input.JsonScan	Json parsing	true	None
spark.rapids.sql.input.OrcScan	ORC parsing	true	None
spark.rapids.sql.input.ParquetScan	Parquet parsing	true	None
spark.rapids.sql.input.AvroScan	Avro parsing	true	None

Partitioning

Name	Description	Default Value	Notes
spark.ra pids.sql.partitioni ng.HashPartitioning	Hash based partitioning	true	None
spark.rap ids.sql.partitionin g.RangePartitioning	Range partitioning	true	None
spark.rapids.s ql.partitioning.Rou ndRobinPartitioning	Round robin partitioning	true	None
spark.ra pids.sql.partitioni ng.SinglePartition$	Single partitioning	true	None