Github user andrewor14 commented on a diff in the pull request:

    https://github.com/apache/spark/pull/7774#discussion_r36045507
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/SparkSQLExecution.scala 
---
    @@ -0,0 +1,84 @@
    +/*
    + * 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.execution
    +
    +import java.util.concurrent.atomic.AtomicLong
    +
    +import org.apache.spark.SparkContext
    +import org.apache.spark.sql.{DataFrame, SQLContext}
    +import org.apache.spark.util.Utils
    +
    +private[sql] object SparkSQLExecution {
    +
    +  val EXECUTION_ID_KEY = "spark.sql.execution.id"
    +
    +  private val _nextExecutionId = new AtomicLong(0)
    +
    +  private def nextExecutionId: Long = _nextExecutionId.getAndIncrement
    +
    +  /**
    +   * Wrap a DataFrame action to track all Spark jobs in the body so that 
we can connect them with
    +   * an execution.
    +   */
    +  def withNewExecution[T](sqlContext: SQLContext, df: DataFrame)(body: => 
T): T = {
    +    val sc = sqlContext.sparkContext
    +    val oldExecutionId = sc.getLocalProperty(EXECUTION_ID_KEY)
    +    try {
    +      if (oldExecutionId == null) {
    +        val executionId = SparkSQLExecution.nextExecutionId
    +        sc.setLocalProperty(EXECUTION_ID_KEY, executionId.toString)
    +        val callSite = Utils.getCallSite()
    +        sqlContext.listener.onExecutionStart(
    +          executionId, callSite.shortForm, callSite.longForm, df, 
System.currentTimeMillis())
    +        val r = body
    +        sqlContext.listener.onExecutionEnd(executionId, 
System.currentTimeMillis())
    +        r
    +      } else {
    +        // Don't support nested `withNewExecution`. This is an example of 
the nested
    +        // `withNewExecution`:
    +        //
    +        // class DataFrame {
    +        //   def foo: T = withNewExecution { 
something.createNewDataFrame().collect() }
    +        // }
    +        //
    +        // Note: `collect` will call withNewExecution
    +        // In this case, only the "executedPlan" for "collect" will be 
executed. The "executedPlan"
    +        // for the outer DataFrame won't be executed. So it's meaningless 
to create a new Execution
    +        // for the outer DataFrame. Even if we track it, since its 
"executedPlan" doesn't run,
    +        // all accumulator metrics will be 0. It will confuse people if we 
show them in Web UI.
    +        //
    +        // A real case is the `DataFrame.count` method.
    +        throw new IllegalArgumentException(s"$EXECUTION_ID_KEY is already 
set")
    --- End diff --
    
    Ah, I get it now. It's because a DF operation might call other DF 
operations internally (e.g. count calls collect) but the user only cares about 
the top level operation (i.e. count, not collect). I think the proper semantics 
should be to inherit the existing execution ID if it already exists. I'm not 
sure if I see why we should throw an exception though.
    
    By the way, I'm confused about one thing, since you didn't wrap `count` in 
`withNewExecution` how did your screenshot display `count` in the call site 
instead of `collect`?


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