使用Spark执行程序查询Cassandra

Question

使用Spark执行程序查询Cassandra

apache-sparkcassandraspark-streamingspark-cassandra-connector

3

我有一个基于kafka流媒体应用，想知道是否有办法在map函数内进行范围查询?

我将来自kafka的消息按时间范围和关键字分组，然后根据这些时间范围和关键字从cassandra中提取数据到该dstream。

类似于:

lookups
  .map(lookup => ((lookup.key, lookup.startTime, lookup.endTime), lookup))
  .groupByKey()
  .transform(rdd => {
    val cassandraSQLContext = new CassandraSQLContext(rdd.context)
    rdd.map(lookupPair => {
      val tableName = //variable based on lookup
      val startTime = aggLookupPair._1._2
      val endTime = aggLookupPair._1._3

      cassandraSQLContext
        .cassandraSql(s"SELECT * FROM ${CASSANDRA_KEYSPACE}.${tableName} WHERE key=${...} AND start_time >= ${startTime} AND start_time < ${endTime};")
        .map(row => {
           //match to {
            case /*case 1*/ => new object1(row)
            case /*case 2*/ =>new object2(row)
          }
        })
        .collect()
    })
  })

这会导致我出现空指针异常：

org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 59.0 failed 1 times, most recent failure: Lost task 0.0 in stage 59.0 (TID 63, localhost): java.lang.NullPointerException
at org.apache.spark.sql.SQLContext.parseSql(SQLContext.scala:231)
at org.apache.spark.sql.cassandra.CassandraSQLContext.cassandraSql(CassandraSQLContext.scala:70)
at RollupFineGrainIngestionService$$anonfun$11$$anonfun$apply$2.apply(MyFile.scala:130)
at RollupFineGrainIngestionService$$anonfun$11$$anonfun$apply$2.apply(MyFile.scala:123)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:370)
at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:285)
at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)

我还尝试过ssc.cassandraTable(CASSANDRA_KEYSPACE, tableName).where("key = ?", ...)...，但是在map内部访问StreamingContext时，Spark会崩溃。

如果有人有任何建议，我将不胜感激。谢谢！

- nickn

1个回答

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- RussS · Accepted Answer

如果您的查询基于分区键，则可以使用joinWithCassandraTable。

但如果您需要更多的灵活性

CassandraConnector(sc.getConf).withSessionDo( session => ...)

这个功能允许您访问执行器上的会话池，并执行任何您想要的操作，而无需管理连接。代码都是可序列化的，并且可以放置在映射中。