org.apache.spark.sql.rapids.ExecutionPlanCaptureCallback.scala Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of rapids-4-spark_2.13 Show documentation
Show all versions of rapids-4-spark_2.13 Show documentation
Creates the distribution package of the RAPIDS plugin for Apache Spark
The newest version!
/*
* Copyright (c) 2022-2023, NVIDIA CORPORATION.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.sql.rapids
import com.nvidia.spark.rapids.ShimLoaderTemp
import org.apache.spark.sql.DataFrame
import org.apache.spark.sql.execution.{QueryExecution, SparkPlan}
import org.apache.spark.sql.util.QueryExecutionListener
trait ExecutionPlanCaptureCallbackBase {
def captureIfNeeded(qe: QueryExecution): Unit
def startCapture(): Unit
def startCapture(timeoutMillis: Long): Unit
def endCapture(): Unit
def endCapture(timeoutMillis: Long): Unit
def getResultsWithTimeout(timeoutMs: Long = 10000): Array[SparkPlan]
def extractExecutedPlan(plan: SparkPlan): SparkPlan
def assertContains(gpuPlan: SparkPlan, className: String): Unit
def assertContains(df: DataFrame, gpuClass: String): Unit
def assertContainsAnsiCast(df: DataFrame): Unit
def assertNotContain(gpuPlan: SparkPlan, className: String): Unit
def assertNotContain(df: DataFrame, gpuClass: String): Unit
def assertDidFallBack(gpuPlan: SparkPlan, fallbackCpuClass: String): Unit
def assertDidFallBack(df: DataFrame, fallbackCpuClass: String): Unit
def assertDidFallBack(gpuPlans: Array[SparkPlan], fallbackCpuClass: String): Unit
def assertCapturedAndGpuFellBack(
// used by python code, should not be Array[String]
fallbackCpuClassList: java.util.ArrayList[String],
timeoutMs: Long): Unit
def assertCapturedAndGpuFellBack(fallbackCpuClass: String, timeoutMs: Long = 2000): Unit
def assertSchemataMatch(cpuDf: DataFrame, gpuDf: DataFrame, expectedSchema: String): Unit
def didFallBack(plan: SparkPlan, fallbackCpuClass: String): Boolean
}
object ExecutionPlanCaptureCallback extends ExecutionPlanCaptureCallbackBase {
lazy val impl = ShimLoaderTemp.newExecutionPlanCaptureCallbackBase()
override def captureIfNeeded(qe: QueryExecution): Unit =
impl.captureIfNeeded(qe)
override def startCapture(): Unit =
impl.startCapture()
override def startCapture(timeoutMillis: Long): Unit =
impl.startCapture(timeoutMillis)
override def endCapture(): Unit = impl.endCapture()
override def endCapture(timeoutMillis: Long): Unit = impl.endCapture(timeoutMillis)
override def getResultsWithTimeout(timeoutMs: Long = 10000): Array[SparkPlan] =
impl.getResultsWithTimeout(timeoutMs)
override def extractExecutedPlan(plan: SparkPlan): SparkPlan =
impl.extractExecutedPlan(plan)
override def assertContains(gpuPlan: SparkPlan, className: String): Unit =
impl.assertContains(gpuPlan, className)
override def assertContains(df: DataFrame, gpuClass: String): Unit =
impl.assertContains(df, gpuClass)
override def assertContainsAnsiCast(df: DataFrame): Unit =
impl.assertContainsAnsiCast(df)
override def assertNotContain(gpuPlan: SparkPlan, className: String): Unit =
impl.assertNotContain(gpuPlan, className)
override def assertNotContain(df: DataFrame, gpuClass: String): Unit =
impl.assertNotContain(df, gpuClass)
override def assertDidFallBack(gpuPlan: SparkPlan, fallbackCpuClass: String): Unit =
impl.assertDidFallBack(gpuPlan, fallbackCpuClass)
override def assertDidFallBack(df: DataFrame, fallbackCpuClass: String): Unit =
impl.assertDidFallBack(df, fallbackCpuClass)
override def assertDidFallBack(gpuPlans: Array[SparkPlan], fallbackCpuClass: String): Unit =
impl.assertDidFallBack(gpuPlans, fallbackCpuClass)
override def assertCapturedAndGpuFellBack(
// used by python code, should not be Array[String]
fallbackCpuClassList: java.util.ArrayList[String],
timeoutMs: Long): Unit =
impl.assertCapturedAndGpuFellBack(fallbackCpuClassList, timeoutMs)
override def assertCapturedAndGpuFellBack(
fallbackCpuClass: String, timeoutMs: Long = 2000): Unit =
impl.assertCapturedAndGpuFellBack(fallbackCpuClass, timeoutMs)
override def assertSchemataMatch(
cpuDf: DataFrame, gpuDf: DataFrame, expectedSchema: String): Unit =
impl.assertSchemataMatch(cpuDf, gpuDf, expectedSchema)
override def didFallBack(plan: SparkPlan, fallbackCpuClass: String): Boolean =
impl.didFallBack(plan, fallbackCpuClass)
}
/**
* Used as a part of testing to capture the executed query plan.
*/
class ExecutionPlanCaptureCallback extends QueryExecutionListener {
override def onSuccess(funcName: String, qe: QueryExecution, durationNs: Long): Unit =
ExecutionPlanCaptureCallback.captureIfNeeded(qe)
override def onFailure(funcName: String, qe: QueryExecution, exception: Exception): Unit =
ExecutionPlanCaptureCallback.captureIfNeeded(qe)
}
trait AdaptiveSparkPlanHelperShim {
def collect[B](p: SparkPlan)(pf: PartialFunction[SparkPlan, B]): Seq[B]
}
© 2015 - 2024 Weber Informatics LLC | Privacy Policy