locationtech / rasterframes

Geospatial Raster support for Spark DataFrames
http://rasterframes.io
Apache License 2.0
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`rasterJoin` easily runs out of memory #401

Closed metasim closed 4 years ago

metasim commented 4 years ago

Haven't yet been able to boil down to a publishable test case.

Stacktrace

java.lang.OutOfMemoryError: Java heap space
    at java.util.Arrays.copyOf(Arrays.java:3236)
    at java.io.ByteArrayOutputStream.toByteArray(ByteArrayOutputStream.java:191)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:262)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
2019-10-30 18:54:13 ERROR SparkUncaughtExceptionHandler:91 - Uncaught exception in thread Thread[Executor task launch worker for task 1407,5,main]
java.lang.OutOfMemoryError: Java heap space
    at java.util.Arrays.copyOf(Arrays.java:3236)
    at java.io.ByteArrayOutputStream.toByteArray(ByteArrayOutputStream.java:191)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:262)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)
2019-10-30 18:54:13 WARN  TaskSetManager:66 - Lost task 172.0 in stage 54.0 (TID 1407, localhost, executor driver): java.lang.OutOfMemoryError: Java heap space
    at java.util.Arrays.copyOf(Arrays.java:3236)
    at java.io.ByteArrayOutputStream.toByteArray(ByteArrayOutputStream.java:191)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:262)
    at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:247)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:836)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:109)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

2019-10-30 18:54:13 ERROR TaskSetManager:70 - Task 172 in stage 54.0 failed 1 times; aborting job
metasim commented 4 years ago

Error is thrown at the end of this function in SparkPlan.scala (org.apache.spark.sql.execution.SparkPlan):

  /**
   * Packing the UnsafeRows into byte array for faster serialization.
   * The byte arrays are in the following format:
   * [size] [bytes of UnsafeRow] [size] [bytes of UnsafeRow] ... [-1]
   *
   * UnsafeRow is highly compressible (at least 8 bytes for any column), the byte array is also
   * compressed.
   */
  private def getByteArrayRdd(n: Int = -1): RDD[(Long, Array[Byte])] = {
    execute().mapPartitionsInternal { iter =>
      var count = 0
      val buffer = new Array[Byte](4 << 10)  // 4K
      val codec = CompressionCodec.createCodec(SparkEnv.get.conf)
      val bos = new ByteArrayOutputStream()
      val out = new DataOutputStream(codec.compressedOutputStream(bos))
      while (iter.hasNext && (n < 0 || count < n)) {
        val row = iter.next().asInstanceOf[UnsafeRow]
        out.writeInt(row.getSizeInBytes)
        row.writeToStream(out, buffer)
        count += 1
      }
      out.writeInt(-1)
      out.flush()
      out.close()
      Iterator((count, bos.toByteArray))
    }
  }
metasim commented 4 years ago

spark.checkpoint.compress is an option. also spark.shuffle.compress.

metasim commented 4 years ago

Turns out the notebook was setting the default driver memory to 512MB.