spark ssc.textFileStream is not streamining any fi

问题:

I am trying to execute below code using eclipse (with maven conf) with 2 worker and each have 2 core or also tried with spark-submit.

public class StreamingWorkCount implements Serializable {

    public static void main(String[] args) {
        Logger.getLogger("org.apache.spark").setLevel(Level.WARN);
        JavaStreamingContext jssc = new JavaStreamingContext(
                "spark://192.168.1.19:7077", "JavaWordCount",
                new Duration(1000));
        JavaDStream<String> trainingData = jssc.textFileStream(
                "/home/bdi-user/kaushal-drive/spark/data/training").cache();
        trainingData.foreach(new Function<JavaRDD<String>, Void>() {

            public Void call(JavaRDD<String> rdd) throws Exception {
                List<String> output = rdd.collect();
                System.out.println("Sentences Collected from files " + output);
                return null;
            }
        });

        trainingData.print();
        jssc.start();
        jssc.awaitTermination();
    }
}

And log of that code

15/01/22 21:57:13 INFO FileInputDStream: New files at time 1421944033000 ms:

15/01/22 21:57:13 INFO JobScheduler: Added jobs for time 1421944033000 ms
15/01/22 21:57:13 INFO JobScheduler: Starting job streaming job 1421944033000 ms.0 from job set of time 1421944033000 ms
15/01/22 21:57:13 INFO SparkContext: Starting job: foreach at StreamingKMean.java:33
15/01/22 21:57:13 INFO DAGScheduler: Job 3 finished: foreach at StreamingKMean.java:33, took 0.000094 s
Sentences Collected from files []
-------------------------------------------
15/01/22 21:57:13 INFO JobScheduler: Finished job streaming job 1421944033000 ms.0 from job set of time 1421944033000 ms
Time: 1421944033000 ms
-------------------------------------------15/01/22 21:57:13 INFO JobScheduler: Starting job streaming job 1421944033000 ms.1 from job set of time 1421944033000 ms


15/01/22 21:57:13 INFO JobScheduler: Finished job streaming job 1421944033000 ms.1 from job set of time 1421944033000 ms
15/01/22 21:57:13 INFO JobScheduler: Total delay: 0.028 s for time 1421944033000 ms (execution: 0.013 s)
15/01/22 21:57:13 INFO MappedRDD: Removing RDD 5 from persistence list
15/01/22 21:57:13 INFO BlockManager: Removing RDD 5
15/01/22 21:57:13 INFO FileInputDStream: Cleared 0 old files that were older than 1421943973000 ms: 
15/01/22 21:57:13 INFO FileInputDStream: Cleared 0 old files that were older than 1421943973000 ms: 
15/01/22 21:57:13 INFO ReceivedBlockTracker: Deleting batches ArrayBuffer()

The Problem is that, i am not getting data form the file which is in the directory. Please help me.

回答1:

Try it with another directory and then copy these files to that directory, while the job is running.

回答2:

had the same problem. Here is my code:

lines = jssc.textFileStream("file:///Users/projects/spark/test/data');

the TextFileSTream is very sensitive; what i ended up doing was:

1. Run Spark program
2. touch datafile
3. mv datafile datafile2
4. mv datafile2  /Users/projects/spark/test/data

and that did it.

回答3:

I think you need to add the scheme, i.e. file:// or hdfs:// in front of your path.

---

Undoing the edit to my comment because: It is in fact file:// and hdfs:// which needs to be added "in front of" the path, so the total path becomes file:///tmp/file.txt or hdfs:///user/data. If there is no NameNode set in the configuration, the latter needs to be hdfs://host:port/user/data.

回答4:

JavaDoc suggests function only streams new files.

Ref: https://spark.apache.org/docs/1.0.1/api/java/org/apache/spark/streaming/api/java/JavaStreamingContext.html#textFileStream(java.lang.String)

Create an input stream that monitors a Hadoop-compatible filesystem for new files and reads them as text files (using key as LongWritable, value as Text and input format as TextInputFormat). Files must be written to the monitored directory by "moving" them from another location within the same file system. File names starting with . are ignored.

回答5:

textFileStream can only monitor a folder when the files in the folder are being added or updated.

If you just want to read files, you can rather use SparkContext.textFile.

回答6:

You have to take in count that Spark Streaming will only read the new files in the directory, no the updated ones (once they are in the directory) and also they all must have the same format.

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