Question

我有一个关于kafka的流媒体应用程序，我想知道是否有办法在地图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。

类似的东西：

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)

我还尝试过ssc.cassandraTable(CASSANDRA_KEYSPACE, tableName).where("key = ?", ...)...，但在尝试访问地图内的StreamingContext时会引发崩溃。

如果有人有任何建议，我将不胜感激。谢谢！

Answer 1

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 => ...)

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，可以放在地图中。

从spark执行器查询cassandra

1 个答案: