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Adding additional functionalities to profiling tool (#2469)
* Adding additional functionalities to profiling tool Signed-off-by: Niranjan Artal <[email protected]> * addressed review comments Signed-off-by: Niranjan Artal <[email protected]>
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rapids-4-spark-tools/src/main/scala/com/nvidia/spark/rapids/tool/profiling/Analysis.scala
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| /* | ||
| * Copyright (c) 2021, 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. | ||
| */ | ||
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| package com.nvidia.spark.rapids.tool.profiling | ||
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| import scala.collection.mutable.ArrayBuffer | ||
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| import org.apache.spark.sql.DataFrame | ||
| import org.apache.spark.sql.rapids.tool.profiling._ | ||
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| /** | ||
| * Does analysis on the DataFrames | ||
| * from object of ApplicationInfo | ||
| */ | ||
| class Analysis(apps: ArrayBuffer[ApplicationInfo]) { | ||
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| require(apps.nonEmpty) | ||
| private val fileWriter = apps.head.fileWriter | ||
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| // Job Level TaskMetrics Aggregation | ||
| def jobMetricsAggregation(): Unit = { | ||
| if (apps.size == 1) { | ||
| fileWriter.write("Job level aggregated task metrics:") | ||
| apps.head.runQuery(apps.head.jobMetricsAggregationSQL + " order by Duration desc") | ||
| } else { | ||
| var query = "" | ||
| for (app <- apps) { | ||
| if (query.isEmpty) { | ||
| query += app.jobMetricsAggregationSQL | ||
| } else { | ||
| query += " union " + app.jobMetricsAggregationSQL | ||
| } | ||
| } | ||
| fileWriter.write("Job level aggregated task metrics:") | ||
| apps.head.runQuery(query + " order by appIndex, Duration desc") | ||
| } | ||
| } | ||
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| // Stage Level TaskMetrics Aggregation | ||
| def stageMetricsAggregation(): Unit = { | ||
| if (apps.size == 1) { | ||
| fileWriter.write("Stage level aggregated task metrics:") | ||
| apps.head.runQuery(apps.head.stageMetricsAggregationSQL + " order by Duration desc") | ||
| } else { | ||
| var query = "" | ||
| for (app <- apps) { | ||
| if (query.isEmpty) { | ||
| query += app.stageMetricsAggregationSQL | ||
| } else { | ||
| query += " union " + app.stageMetricsAggregationSQL | ||
| } | ||
| } | ||
| fileWriter.write("Stage level aggregated task metrics:") | ||
| apps.head.runQuery(query + " order by appIndex, Duration desc") | ||
| } | ||
| } | ||
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| // Job + Stage Level TaskMetrics Aggregation | ||
| def jobAndStageMetricsAggregation(): Unit = { | ||
| if (apps.size == 1) { | ||
| val messageHeader = "Job + Stage level aggregated task metrics:" | ||
| apps.head.runQuery(apps.head.jobAndStageMetricsAggregationSQL + " order by Duration desc") | ||
| } else { | ||
| var query = "" | ||
| for (app <- apps) { | ||
| if (query.isEmpty) { | ||
| query += app.jobAndStageMetricsAggregationSQL | ||
| } else { | ||
| query += " union " + app.jobAndStageMetricsAggregationSQL | ||
| } | ||
| } | ||
| fileWriter.write("Job + Stage level aggregated task metrics:") | ||
| apps.head.runQuery(query + " order by appIndex, Duration desc") | ||
| } | ||
| } | ||
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| // SQL Level TaskMetrics Aggregation(Only when SQL exists) | ||
| def sqlMetricsAggregation(): DataFrame = { | ||
| if (apps.size == 1) { | ||
| if (apps.head.allDataFrames.contains(s"sqlDF_${apps.head.index}")) { | ||
| val messageHeader = "SQL level aggregated task metrics:" | ||
| apps.head.runQuery(apps.head.sqlMetricsAggregationSQL + " order by Duration desc") | ||
| } else { | ||
| apps.head.sparkSession.emptyDataFrame | ||
| } | ||
| } else { | ||
| var query = "" | ||
| val appsWithSQL = apps.filter(p => p.allDataFrames.contains(s"sqlDF_${p.index}")) | ||
| for (app <- appsWithSQL) { | ||
| if (query.isEmpty) { | ||
| query += app.sqlMetricsAggregationSQL | ||
| } else { | ||
| query += " union " + app.sqlMetricsAggregationSQL | ||
| } | ||
| } | ||
| val messageHeader = "SQL level aggregated task metrics:" | ||
| apps.head.runQuery(query + " order by appIndex, Duration desc") | ||
| } | ||
| } | ||
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| // custom query execution. Normally for debugging use. | ||
| def customQueryExecution(app: ApplicationInfo): Unit = { | ||
| fileWriter.write("Custom query execution:") | ||
| val customQuery = | ||
| s"""select stageId from stageDF_${app.index} limit 1 | ||
| |""".stripMargin | ||
| app.runQuery(customQuery) | ||
| } | ||
| } |
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