[jira] [Created] (KUDU-3205) NPE in KuduScanTokenBuilder#build after a tablet server goes down

["Junegunn Choi (Jira)" <ji...@apache.org>]

Junegunn Choi created KUDU-3205:
-----------------------------------

             Summary: NPE in KuduScanTokenBuilder#build after a tablet server goes down
                 Key: KUDU-3205
                 URL: https://issues.apache.org/jira/browse/KUDU-3205
             Project: Kudu
          Issue Type: Bug
          Components: spark
    Affects Versions: 1.13.0
            Reporter: Junegunn Choi


When a tablet server goes down while running a query on Spark, the connection becomes unusable due to the cached tablet locations that have become stale.
h2. Steps to reproduce
h3. Start spark-shell with kudu-spark2 1.13.0

The problem is not reproducible with kudu-spark2 1.12.0 or below, because it was introduced in [KUDU-1802 |https://github.com/apache/kudu/commit/d23ee5d38ddc4317f431dd65df0c825c00cc968a].
h3. Run a scan query
{code:scala}
import org.apache.kudu.spark.kudu._
val dummy = spark.read.options(Map("kudu.master" -> kuduMasters, "kudu.table" -> "dummy")).kudu
dummy.createOrReplaceTempView("dummy")

spark.sql("select sum(id), min(val2), max(val2), count(*) from dummy").show
{code}
h3. Kill a tablet server

Kill one of the tablet servers that are serving data for the query. The query should fail immediately.
{noformat}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 0.0 failed 1 times, mo
st recent failure: Lost task 2.0 in stage 0.0 (TID 2, localhost, executor driver): java.lang.RuntimeException: org.apache.kudu.client.NonRecoverableException: Scanner *** not found (it may have expired)
{noformat}
h3. Re-run the query
{code:scala}
spark.sql("select sum(id), min(val2), max(val2), count(*) from dummy").show
{code}
Doesn't work, fails with an NPE.
{noformat}
Caused by: java.lang.RuntimeException: java.lang.NullPointerException
  at org.apache.kudu.client.KuduScanToken$KuduScanTokenBuilder.build(KuduScanToken.java:697)
  at org.apache.kudu.spark.kudu.KuduRDD.getPartitions(KuduRDD.scala:95)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:273)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:269)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:269)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:273)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:269)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:269)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:273)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:269)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:269)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:273)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:269)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:269)
  at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:273)
  at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:269)
  at scala.Option.getOrElse(Option.scala:121)
  at org.apache.spark.rdd.RDD.partitions(RDD.scala:269)
  at org.apache.spark.ShuffleDependency.<init>(Dependency.scala:94)
  at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.prepareShuffleDependency(ShuffleExchangeExec.scala:323)
  at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec.prepareShuffleDependency(ShuffleExchangeExec.scala:91)
  at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:128)
  at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$$anonfun$doExecute$1.apply(ShuffleExchangeExec.scala:119)
  at org.apache.spark.sql.catalyst.errors.package$.attachTree(package.scala:52)
  ... 86 more
Caused by: java.lang.NullPointerException
  at org.apache.kudu.client.KuduScanToken$KuduScanTokenBuilder.build(KuduScanToken.java:674)
  ... 117 more
{noformat}
Re-creating the DataFrame doesn't help:
{code:scala}
val dummy = spark.read.options(Map("kudu.master" -> kuduMasters, "kudu.table" -> "dummy")).kudu
dummy.createOrReplaceTempView("dummy")

// Still fails with an NPE
spark.sql("select sum(id), min(val2), max(val2), count(*) from dummy").show
{code}
h2. Cause
{code:java|title=KuduScanToken.java:666}
// Build the list of replica metadata.
List<Client.TabletMetadataPB.ReplicaMetadataPB> replicas = new ArrayList<>();
for (LocatedTablet.Replica replica : remoteTablet.getReplicas()) {
  Integer serverIndex = serverIndexMap.get(
      new HostAndPort(replica.getRpcHost(), replica.getRpcPort()));
  Client.TabletMetadataPB.ReplicaMetadataPB.Builder tabletMetadataBuilder =
      Client.TabletMetadataPB.ReplicaMetadataPB.newBuilder()
          .setRole(replica.getRoleAsEnum())
          .setTsIdx(serverIndex);
  if (replica.getDimensionLabel() != null) {
    tabletMetadataBuilder.setDimensionLabel(replica.getDimensionLabel());
  }
  replicas.add(tabletMetadataBuilder.build());
}
{code}
{{serverIndex}} can be null here, because we're using the cached tablet locations that are stale now ({{TableLocationsCache.Entry}}).
h2. Workarounds
 - Restart Spark shell
 - Wait until the connection becomes idle and cleaned up
{noformat}
DEBUG Connection: [peer master-***] handling channelInactive
20/10/26 10:37:54 DEBUG Connection: [peer master-***] cleaning up while in state READY due to: connection closed
{noformat}

 - Use kudu-spark2 1.12.0 or below



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