@@ -43,8 +43,8 @@ class PythonDStream[T: ClassTag](
4343 preservePartitoning : Boolean ,
4444 pythonExec : String ,
4545 broadcastVars : JList [Broadcast [Array [Byte ]]],
46- accumulator : Accumulator [JList [Array [Byte ]]])
47- extends DStream [Array [Byte ]](parent.ssc) {
46+ accumulator : Accumulator [JList [Array [Byte ]]]
47+ ) extends DStream [Array [Byte ]](parent.ssc) {
4848
4949 override def dependencies = List (parent)
5050
@@ -70,8 +70,10 @@ class PythonDStream[T: ClassTag](
7070}
7171
7272
73- private class PythonPairwiseDStream (prev: DStream [Array [Byte ]], partitioner : Partitioner ) extends
74- DStream [Array [Byte ]](prev.ssc){
73+ private class PythonPairwiseDStream (
74+ prev: DStream [Array [Byte ]],
75+ partitioner : Partitioner
76+ ) extends DStream [Array [Byte ]](prev.ssc){
7577 override def dependencies = List (prev)
7678
7779 override def slideDuration : Duration = prev.slideDuration
@@ -116,14 +118,14 @@ class PythonForeachDStream(
116118
117119/**
118120 * This is a input stream just for the unitest. This is equivalent to a checkpointable,
119- * replayable, reliable message queue like Kafka. It requires a JArrayList input of JavaRDD,
121+ * replayable, reliable message queue like Kafka. It requires a JArrayList of JavaRDD,
120122 * and returns the i_th element at the i_th batch under manual clock.
121123 */
122124
123125class PythonTestInputStream (
124126 ssc_ : JavaStreamingContext ,
125- inputRDDs : JArrayList [JavaRDD [Array [Byte ]]])
126- extends InputDStream [Array [Byte ]](JavaStreamingContext .toStreamingContext(ssc_)) {
127+ inputRDDs : JArrayList [JavaRDD [Array [Byte ]]]
128+ ) extends InputDStream [Array [Byte ]](JavaStreamingContext .toStreamingContext(ssc_)) {
127129
128130 def start () {}
129131
@@ -146,4 +148,4 @@ class PythonTestInputStream(
146148 }
147149
148150 val asJavaDStream = JavaDStream .fromDStream(this )
149- }
151+ }
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