用java,scala,python三种语言实现spark rdd的glom算子
时间: 2024-05-05 11:16:13 浏览: 160
Java实现:
```java
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import scala.Tuple2;
import java.util.ArrayList;
import java.util.List;
public class GlomExample {
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("GlomExample").setMaster("local");
JavaSparkContext sc = new JavaSparkContext(conf);
List<Integer> data = new ArrayList<>();
for (int i = 1; i <= 10; i++) {
data.add(i);
}
JavaRDD<Integer> rdd = sc.parallelize(data, 2);
JavaRDD<List<Integer>> glomRdd = rdd.glom();
List<List<Integer>> result = glomRdd.collect();
for (int i = 0; i < result.size(); i++) {
System.out.println("Partition " + i + ": " + result.get(i));
}
sc.stop();
}
}
```
Scala实现:
```scala
import org.apache.spark.{SparkConf, SparkContext}
object GlomExample {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("GlomExample").setMaster("local")
val sc = new SparkContext(conf)
val data = 1 to 10
val rdd = sc.parallelize(data, 2)
val glomRdd = rdd.glom()
val result = glomRdd.collect()
for (i <- result.indices) {
println(s"Partition $i: ${result(i).toList}")
}
sc.stop()
}
}
```
Python实现:
```python
from pyspark import SparkConf, SparkContext
conf = SparkConf().setAppName("GlomExample").setMaster("local")
sc = SparkContext(conf=conf)
data = range(1, 11)
rdd = sc.parallelize(data, 2)
glom_rdd = rdd.glom()
result = glom_rdd.collect()
for i in range(len(result)):
print(f"Partition {i}: {list(result[i])}")
sc.stop()
```