cloud-fan commented on a change in pull request #33422: URL: https://github.com/apache/spark/pull/33422#discussion_r672777257
########## File path: sql/core/src/main/scala/org/apache/spark/sql/Observation.scala ########## @@ -0,0 +1,150 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You 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 + +import java.util.UUID + +import org.apache.spark.sql.execution.QueryExecution +import org.apache.spark.sql.util.QueryExecutionListener + + +/** + * Helper class to simplify usage of `Dataset.observe(String, Column, Column*)`: + * + * {{{ + * // Observe row count (rows) and highest id (maxid) in the Dataset while writing it + * val observation = Observation("my metrics") + * val observed_ds = ds.observe(observation, count(lit(1)).as("rows"), max($"id").as("maxid")) + * observed_ds.write.parquet("ds.parquet") + * val metrics = observation.get + * }}} + * + * This collects the metrics while the first action is executed on the observed dataset. Subsequent + * actions do not modify the metrics returned by [[get]]. Retrieval of the metric via [[get]] + * blocks until the first action has finished and metrics become available. + * + * This class does not support streaming datasets. + * + * @param name name of the metric + * @since 3.3.0 + */ +class Observation(name: String) { + + private val listener: ObservationListener = ObservationListener(this) + + @volatile private var sparkSession: Option[SparkSession] = None + + @volatile private var row: Option[Row] = None + + /** + * Attach this observation to the given [[Dataset]] to observe aggregation expressions. + * + * @param ds dataset + * @param expr first aggregation expression + * @param exprs more aggregation expressions + * @tparam T dataset type + * @return observed dataset + * @throws IllegalArgumentException If this is a streaming Dataset (ds.isStreaming == true) + */ + private[spark] def on[T](ds: Dataset[T], expr: Column, exprs: Column*): Dataset[T] = { + if (ds.isStreaming) { + throw new IllegalArgumentException("Observation does not support streaming Datasets") + } + register(ds.sparkSession) + ds.observe(name, expr, exprs: _*) + } + + /** + * Get the observed metrics. This waits for the observed dataset to finish its first action. + * Only the result of the first action is available. Subsequent actions do not modify the result. + * + * @return the observed metrics as a [[Row]] + * @throws InterruptedException interrupted while waiting + */ + @throws[InterruptedException] + def get: Row = { + synchronized { + // we need to loop as wait might return without us calling notify + // https://en.wikipedia.org/w/index.php?title=Spurious_wakeup&oldid=992601610 + while (this.row.isEmpty) { + wait() + } + } + + this.row.get + } + + private def register(sparkSession: SparkSession): Unit = { + // makes this class thread-safe: + // only the first thread entering this block can set sparkSession + // all other threads will see the exception, as it is only allowed to do this once + synchronized { + if (this.sparkSession.isDefined) { + throw new IllegalArgumentException("An Observation can be used with a Dataset only once") + } + this.sparkSession = Some(sparkSession) + } + + sparkSession.listenerManager.register(this.listener) + } + + private def unregister(): Unit = { + this.sparkSession.foreach(_.listenerManager.unregister(this.listener)) + } + + private[spark] def onFinish(qe: QueryExecution): Unit = { + synchronized { + if (this.row.isEmpty) { + this.row = qe.observedMetrics.get(name) + if (this.row.isDefined) { + notifyAll() + unregister() + } + } + } + } + +} + +private[sql] case class ObservationListener(observation: Observation) + extends QueryExecutionListener { + + override def onSuccess(funcName: String, qe: QueryExecution, durationNs: Long): Unit = + observation.onFinish(qe) + + override def onFailure(funcName: String, qe: QueryExecution, exception: Exception): Unit = + observation.onFinish(qe) + +} + +/** + * (Scala-specific) Create a named or anonymous instance of Observation. + */ +object Observation { + + /** + * Observation constructor for creating an anonymous observation. + */ + def apply(): Observation = new Observation(UUID.randomUUID().toString) Review comment: shall we also add a default parameter in the constructor? then java users can also get benefits. -- This is an automated message from the Apache Git Service. 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