spark中三种分区模式示例
时间: 2023-10-27 08:16:39 浏览: 49
1. Hash分区模式:将数据按照hash值进行分区,保证相同的key在同一个分区中,适用于数据分布比较均匀的场景。
例如:
```
val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c"), (4, "d")))
val partitionedRdd = rdd.partitionBy(new HashPartitioner(2))
```
2. Range分区模式:将数据按照一定的范围进行分区,适用于数据分布比较不均匀的场景。
例如:
```
val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c"), (4, "d")))
val partitionedRdd = rdd.partitionBy(new RangePartitioner(2, rdd))
```
3. 自定义分区模式:根据自定义的逻辑对数据进行分区,适用于特定的业务场景。
例如:
```
class CustomPartitioner(numParts: Int) extends Partitioner {
override def numPartitions: Int = numParts
override def getPartition(key: Any): Int = {
val k = key.asInstanceOf[Int]
if (k % 2 == 0) 0 else 1
}
}
val rdd = sc.parallelize(Seq((1, "a"), (2, "b"), (3, "c"), (4, "d")))
val partitionedRdd = rdd.partitionBy(new CustomPartitioner(2))
```