使用spark在Cassandra Column Families上执行SQL查询的不同方法之间的比较

时间:2015-06-22 10:53:31

标签: java cassandra apache-spark apache-spark-sql spark-cassandra-connector

作为我项目的一部分,我必须为一个非常大的Cassandra数据集创建一个SQL查询接口,因此我一直在寻找使用Spark在cassandra列系列上执行SQL查询的不同方法,我提出了3种不同的方法方法

  1. 使用带有静态定义架构的Spark SQLContext

    // statically defined in the application
    public static class TableTuple implements Serializable {
        private int id;
        private String line;
    
        TableTuple (int i, String l) {
            id = i;
            line = l;
        }
    
        // getters and setters
        ...
    }
    

    我将定义用作:

    SparkConf conf = new SparkConf(true)
            .set("spark.cassandra.connection.host", CASSANDRA_HOST)
            .setJars(jars);
    
    SparkContext sc = new SparkContext(HOST, APP_NAME, conf);
    SQLContext sqlContext = new SQLContext(sc);
    
    JavaRDD<CassandraRow> rowrdd = javaFunctions(sc).cassandraTable(CASSANDRA_KEYSPACE, CASSANDRA_COLUMN_FAMILY);
    JavaRDD<TableTuple> rdd = rowrdd.map(row -> new TableTuple(row.getInt(0), row.getString(1)));
    
    DataFrame dataFrame = sqlContext.createDataFrame(rdd, TableTuple.class);
    dataFrame.registerTempTable("lines");
    
    DataFrame resultsFrame = sqlContext.sql("Select line from lines where id=1");
    
    System.out.println(Arrays.asList(resultsFrame.collect()));
    
  2. 使用带有动态定义架构的Spark SQLContext

    SparkConf conf = new SparkConf(true)
            .set("spark.cassandra.connection.host", CASSANDRA_HOST)
            .setJars(jars);
    
    SparkContext sc = new SparkContext(HOST, APP_NAME, conf);
    SQLContext sqlContext = new SQLContext(sc);
    
    JavaRDD<CassandraRow> cassandraRdd = javaFunctions(sc).cassandraTable(CASSANDRA_KEYSPACE, CASSANDRA_COLUMN_FAMILY);
    JavaRDD<Row> rdd = cassandraRdd.map(row -> RowFactory.create(row.getInt(0), row.getString(1)));
    
    List<StructField> fields = new ArrayList<>();
    fields.add(DataTypes.createStructField("id", DataTypes.IntegerType, true));
    fields.add(DataTypes.createStructField("line", DataTypes.StringType, true));
    StructType schema = DataTypes.createStructType(fields);
    
    DataFrame dataFrame = sqlContext.createDataFrame(rdd, schema);
    dataFrame.registerTempTable("lines");
    
    DataFrame resultDataFrame = sqlContext.sql("select line from lines where id = 1");
    
    System.out.println(Arrays.asList(resultDataFrame.collect()));
    
  3. 使用spark-cassandra-connector中的CassandraSQLContext

    SparkConf conf = new SparkConf(true)
            .set("spark.cassandra.connection.host", CASSANDRA_HOST)
            .setJars(jars);
    
    SparkContext sc = new SparkContext(HOST, APP_NAME, conf);
    
    CassandraSQLContext sqlContext = new CassandraSQLContext(sc);
    DataFrame resultsFrame = sqlContext.sql("Select line from " + CASSANDRA_KEYSPACE + "." + CASSANDRA_COLUMN_FAMILY + " where id = 1");
    
    System.out.println(Arrays.asList(resultsFrame.collect()));
    
  4. 我想知道一种方法优于另一种方法的优点/缺点。此外,对于CassandraSQLContext方法,查询仅限于CQL,或者它与Spark SQL完全兼容。我还想对我的特定用例进行分析,我有一个cassandra列系列,有大约1760万个元组,有62列。对于查询这么大的数据库,哪种方法最合适?

0 个答案:

没有答案