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从spark Actuator 查询cassandra

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我有一个kafka的流媒体应用程序,我想知道是否有办法从 Map 功能中进行范围查询?

我按照时间范围和密钥对来自kafka的消息进行分组,然后根据我想将数据从cassandra拉入该dstream的时间范围和密钥 .

就像是:

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()
    })
  })

这给了我一个空指针异常:

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)

我也尝试过 ssc.cassandraTable(CASSANDRA_KEYSPACE, tableName).where("key = ?", ...)... 但在尝试访问 Map 内的StreamingContext时会引发崩溃 .

如果有人有任何建议,我将不胜感激 . 谢谢!

1 回答

  • 2

    如果您的查询基于分区键,则可能需要使用 joinWithCassandraTable .

    但如果你需要更多的灵活性

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

    将允许您访问执行程序上的会话池并执行您想要的任何操作而无需管理连接 . 代码都是可序列化的,可以放在 Map 中 .

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