After moving the setting of the parameter to SparkConf initialization instead
of after the context is already initialized, I have it operating reliably on
local filesystem, but not on hdfs. Are there any differences in behavior
between these two cases I should be aware of?
I don’t usually mailinglist or exchange, so forgive me for my ignorance of
whether this message will go horribly wrong due to formatting.
I plan to port the following code to Hadoop FS API to generalize testing to
understand actual behavior and ensure desired behavior.
public static JavaDStream<String>
textFileStreamIncludingExisting(JavaStreamingContext context, String path)
{
return context.fileStream(path, LongWritable
.class, Text.class, TextInputFormat.class, v1 -> true,
false).map(v1 -> v1._2.toString());
}
@Test
public void testTextFileStreamIncludingExistingReadsOldFiles() throws Exception
{
final Path testDir = Files.createTempDirectory("sparkTest");
final ArrayList<Path> tempFiles = new ArrayList();
// create 20 "old" files
final int testFileNumberLimit = 20;
for (int testFileNumber = 0; testFileNumber < testFileNumberLimit;
testFileNumber++)
{
final Path testFile = Files.createTempFile(testDir, "testFile", "");
tempFiles.add(testFile);
final FileWriter fileWriter = new FileWriter(testFile.toFile());
fileWriter.write("asdf");
fileWriter.flush();
fileWriter.close();
for (String eachAttribute : new String[]{"basic:lastAccessTime",
"basic:lastModifiedTime",
"basic:creationTime"})
{ // set file dates 0 to 20 days ago
Files.setAttribute(testFile, eachAttribute,
FileTime.from(Instant.now().minus(Duration.ofDays
(testFileNumber))));
}
}
final SparkConf sparkConf = new
SparkConf().setMaster("local[1]").setAppName("test");
sparkConf.set("spark.streaming.minRememberDuration",
String.valueOf(Integer.MAX_VALUE));
final JavaStreamingContext context = new JavaStreamingContext(sparkConf,
Durations.seconds(1));
final JavaDStream<String> input =
SparkUtil.textFileStreamIncludingExisting(context, String.valueOf(testDir
.toUri()));
// count files read
final Accumulator<Integer> accumulator =
context.sparkContext().accumulator(0);
// setup async wait
Semaphore done = new Semaphore(1);
done.acquire();
input.foreachRDD(new Function<JavaRDD<String>, Void>()
{
@Override
public Void call(JavaRDD<String> v1) throws Exception
{
if (v1.count() == 0)
{
done.release();
}
accumulator.add((int) v1.count());
return null;
}
});
context.start();
// wait for completion or 20 sec
done.tryAcquire(20, TimeUnit.SECONDS);
context.stop();
assertThat(accumulator.value(), is(testFileNumberLimit));
for (Path eachTempFile : tempFiles)
{
Files.deleteIfExists(eachTempFile);
}
Files.deleteIfExists(testDir);
}
From: Tathagata Das [mailto:t...@databricks.com]
Sent: Wednesday, July 15, 2015 00:01
To: Terry Hole
Cc: Hunter Morgan; user@spark.apache.org
Subject: Re: fileStream with old files
It was added, but its not documented publicly. I am planning to change the name
of the conf to spark.streaming.fileStream.minRememberDuration to make it easier
to understand
On Mon, Jul 13, 2015 at 9:43 PM, Terry Hole
<hujie.ea...@gmail.com<mailto:hujie.ea...@gmail.com>> wrote:
A new configuration named spark.streaming.minRememberDuration was added since
1.2.1 to control the file stream input, the default value is 60 seconds, you
can change this value to a large value to include older files (older than 1
minute)
You can get the detail from this jira:
https://issues.apache.org/jira/browse/SPARK-3276
-Terry
On Tue, Jul 14, 2015 at 4:44 AM, automaticgiant
<hunter.mor...@rackspace.com<mailto:hunter.mor...@rackspace.com>> wrote:
It's not as odd as it sounds. I want to ensure that long streaming job
outages can recover all the files that went into a directory while the job
was down.
I've looked at
http://apache-spark-user-list.1001560.n3.nabble.com/Generating-a-DStream-by-existing-textfiles-td20030.html#a20039
and
http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Streaming-td14306.html#a16435
and
https://stackoverflow.com/questions/29022379/spark-streaming-hdfs/29036469#29036469?newreg=e7e25469132d4fbc8350be8f876cf81e
, but all seem unhelpful.
I've tested combinations of the following:
* fileStreams created with dumb accept-all filters
* newFilesOnly true and false,
* tweaking minRememberDuration to high and low values,
* on hdfs or local directory.
The problem is that it will not read files in the directory from more than a
minute ago.
JavaPairInputDStream<LongWritable, Text> input = context.fileStream(indir,
LongWritable.class, Text.class, TextInputFormat.class, v -> true, false);
Also tried with having set:
context.sparkContext().getConf().set("spark.streaming.minRememberDuration",
"1654564"); to big/small.
Are there known limitations of the onlyNewFiles=false? Am I doing something
wrong?
--
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