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com.datastax.spark.connector

SparkContextFunctions

class SparkContextFunctions extends Serializable

Provides Cassandra-specific methods on SparkContext

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Instance Constructors

  1. new SparkContextFunctions(sc: SparkContext)

Value Members

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  5. def cassandraTable[T](keyspace: String, table: String)(implicit connector: CassandraConnector = CassandraConnector(sc), readConf: ReadConf = ReadConf.fromSparkConf(sc.getConf), ct: ClassTag[T], rrf: RowReaderFactory[T], ev: ValidRDDType[T]): CassandraTableScanRDD[T]

    Returns a view of a Cassandra table as CassandraRDD.

    Returns a view of a Cassandra table as CassandraRDD. This method is made available on SparkContext by importing com.datastax.spark.connector._

    Depending on the type parameter passed to cassandraTable, every row is converted to one of the following:

    • an CassandraRow object (default, if no type given)
    • a tuple containing column values in the same order as columns selected by CassandraRDD#select
    • object of a user defined class, populated by appropriate ColumnMapper

    Example:

    CREATE KEYSPACE test WITH replication = {'class': 'SimpleStrategy', 'replication_factor': 1 };
    CREATE TABLE test.words (word text PRIMARY KEY, count int);
    INSERT INTO test.words (word, count) VALUES ('foo', 20);
    INSERT INTO test.words (word, count) VALUES ('bar', 20);
    ...
    // Obtaining RDD of CassandraRow objects:
    val rdd1 = sc.cassandraTable("test", "words")
    rdd1.first.getString("word")  // foo
    rdd1.first.getInt("count")    // 20
    
    // Obtaining RDD of tuples:
    val rdd2 = sc.cassandraTable[(String, Int)]("test", "words").select("word", "count")
    rdd2.first._1  // foo
    rdd2.first._2  // 20
    
    // Obtaining RDD of user defined objects:
    case class WordCount(word: String, count: Int)
    val rdd3 = sc.cassandraTable[WordCount]("test", "words")
    rdd3.first.word  // foo
    rdd3.first.count // 20
  6. def clone(): AnyRef
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  7. def emptyCassandraTable[T](keyspace: String, table: String)(implicit connector: CassandraConnector = CassandraConnector(sc), readConf: ReadConf = ReadConf.fromSparkConf(sc.getConf), ct: ClassTag[T], rrf: RowReaderFactory[T], ev: ValidRDDType[T]): EmptyCassandraRDD[T]

    Produces the empty CassandraRDD which does not perform any validation and it does not even try to return any rows.

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  16. final def notifyAll(): Unit
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  17. val sc: SparkContext
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