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-rw-r--r--core/src/main/scala/spark/RDD.scala26
-rw-r--r--core/src/main/scala/spark/rdd/PipedRDD.scala27
-rw-r--r--core/src/test/scala/spark/PipedRDDSuite.scala39
3 files changed, 83 insertions, 9 deletions
diff --git a/core/src/main/scala/spark/RDD.scala b/core/src/main/scala/spark/RDD.scala
index 7cb9bfebeb..05ff399a7b 100644
--- a/core/src/main/scala/spark/RDD.scala
+++ b/core/src/main/scala/spark/RDD.scala
@@ -14,6 +14,7 @@ import org.apache.hadoop.mapred.TextOutputFormat
import it.unimi.dsi.fastutil.objects.{Object2LongOpenHashMap => OLMap}
+import spark.broadcast.Broadcast
import spark.Partitioner._
import spark.partial.BoundedDouble
import spark.partial.CountEvaluator
@@ -354,13 +355,30 @@ abstract class RDD[T: ClassManifest](
/**
* Return an RDD created by piping elements to a forked external process.
*/
- def pipe(command: Seq[String]): RDD[String] = new PipedRDD(this, command)
+ def pipe(command: String, env: Map[String, String]): RDD[String] =
+ new PipedRDD(this, command, env)
+
/**
* Return an RDD created by piping elements to a forked external process.
- */
- def pipe(command: Seq[String], env: Map[String, String]): RDD[String] =
- new PipedRDD(this, command, env)
+ * How each record in RDD is outputed to the process can be controled by providing a
+ * function trasnform(T, outputFunction: String => Unit). transform() will be called with
+ * the currnet record in RDD as the 1st parameter, and the function to output the record to
+ * the external process (like out.println()) as the 2nd parameter.
+ * Here's an example on how to pipe the RDD data of groupBy() in a streaming way,
+ * instead of constructing a huge String to concat all the records:
+ * def tranform(record:(String, Seq[String]), f:String=>Unit) = for (e <- record._2){f(e)}
+ * pipeContext can be used to transfer additional context data to the external process
+ * besides the RDD. pipeContext is a broadcast Seq[String], each line would be piped to
+ * external process with "^A" as the delimiter in the end of context data. Delimiter can also
+ * be customized by the last parameter delimiter.
+ */
+ def pipe(
+ command: Seq[String],
+ env: Map[String, String] = Map(),
+ printPipeContext: (String => Unit) => Unit = null,
+ printRDDElement: (T, String => Unit) => Unit = null): RDD[String] =
+ new PipedRDD(this, command, env, if (printPipeContext ne null) sc.clean(printPipeContext) else null, printRDDElement)
/**
* Return a new RDD by applying a function to each partition of this RDD.
diff --git a/core/src/main/scala/spark/rdd/PipedRDD.scala b/core/src/main/scala/spark/rdd/PipedRDD.scala
index 962a1b21ad..b2c07891ab 100644
--- a/core/src/main/scala/spark/rdd/PipedRDD.scala
+++ b/core/src/main/scala/spark/rdd/PipedRDD.scala
@@ -9,6 +9,7 @@ import scala.collection.mutable.ArrayBuffer
import scala.io.Source
import spark.{RDD, SparkEnv, Partition, TaskContext}
+import spark.broadcast.Broadcast
/**
@@ -18,14 +19,21 @@ import spark.{RDD, SparkEnv, Partition, TaskContext}
class PipedRDD[T: ClassManifest](
prev: RDD[T],
command: Seq[String],
- envVars: Map[String, String])
+ envVars: Map[String, String],
+ printPipeContext: (String => Unit) => Unit,
+ printRDDElement: (T, String => Unit) => Unit)
extends RDD[String](prev) {
- def this(prev: RDD[T], command: Seq[String]) = this(prev, command, Map())
-
// Similar to Runtime.exec(), if we are given a single string, split it into words
// using a standard StringTokenizer (i.e. by spaces)
- def this(prev: RDD[T], command: String) = this(prev, PipedRDD.tokenize(command))
+ def this(
+ prev: RDD[T],
+ command: String,
+ envVars: Map[String, String] = Map(),
+ printPipeContext: (String => Unit) => Unit = null,
+ printRDDElement: (T, String => Unit) => Unit = null) =
+ this(prev, PipedRDD.tokenize(command), envVars, printPipeContext, printRDDElement)
+
override def getPartitions: Array[Partition] = firstParent[T].partitions
@@ -52,8 +60,17 @@ class PipedRDD[T: ClassManifest](
override def run() {
SparkEnv.set(env)
val out = new PrintWriter(proc.getOutputStream)
+
+ // input the pipe context firstly
+ if ( printPipeContext != null) {
+ printPipeContext(out.println(_))
+ }
for (elem <- firstParent[T].iterator(split, context)) {
- out.println(elem)
+ if (printRDDElement != null) {
+ printRDDElement(elem, out.println(_))
+ } else {
+ out.println(elem)
+ }
}
out.close()
}
diff --git a/core/src/test/scala/spark/PipedRDDSuite.scala b/core/src/test/scala/spark/PipedRDDSuite.scala
index a6344edf8f..ed075f93ec 100644
--- a/core/src/test/scala/spark/PipedRDDSuite.scala
+++ b/core/src/test/scala/spark/PipedRDDSuite.scala
@@ -19,6 +19,45 @@ class PipedRDDSuite extends FunSuite with LocalSparkContext {
assert(c(3) === "4")
}
+ test("advanced pipe") {
+ sc = new SparkContext("local", "test")
+ val nums = sc.makeRDD(Array(1, 2, 3, 4), 2)
+ val bl = sc.broadcast(List("0"))
+
+ val piped = nums.pipe(Seq("cat"),
+ Map[String, String](),
+ (f: String => Unit) => {bl.value.map(f(_));f("\u0001")},
+ (i:Int, f: String=> Unit) => f(i + "_"))
+
+ val c = piped.collect()
+
+ assert(c.size === 8)
+ assert(c(0) === "0")
+ assert(c(1) === "\u0001")
+ assert(c(2) === "1_")
+ assert(c(3) === "2_")
+ assert(c(4) === "0")
+ assert(c(5) === "\u0001")
+ assert(c(6) === "3_")
+ assert(c(7) === "4_")
+
+ val nums1 = sc.makeRDD(Array("a\t1", "b\t2", "a\t3", "b\t4"), 2)
+ val d = nums1.groupBy(str=>str.split("\t")(0)).
+ pipe(Seq("cat"),
+ Map[String, String](),
+ (f: String => Unit) => {bl.value.map(f(_));f("\u0001")},
+ (i:Tuple2[String, Seq[String]], f: String=> Unit) => {for (e <- i._2){ f(e + "_")}}).collect()
+ assert(d.size === 8)
+ assert(d(0) === "0")
+ assert(d(1) === "\u0001")
+ assert(d(2) === "b\t2_")
+ assert(d(3) === "b\t4_")
+ assert(d(4) === "0")
+ assert(d(5) === "\u0001")
+ assert(d(6) === "a\t1_")
+ assert(d(7) === "a\t3_")
+ }
+
test("pipe with env variable") {
sc = new SparkContext("local", "test")
val nums = sc.makeRDD(Array(1, 2, 3, 4), 2)
generated by cgit v1.2.3 (git 2.39.1) at 2024-09-19 16:20:32 +0000