Hi Joe,
Thanks for reporting back. So, it indeed seems the same problem as for OLAP traversals: input splits of HBaseInutFormat have the size of a complete region which is a bit too much for SparkGraphComputer. I think it should be fairly easy to adapt JanusGraph->HBaseInputFormat a bit, such that the splits coming from parent HBase->TableInputFormat are split in smaller parts, let's say smaller than some configurable janusgraph.hbase.mapreduce.maxinputsplitsize=128M. All the necessary variables and methods are present in HBase->TableInputFormat. I plan to do it some time in the future, but please do not rely on it. If someone else wants to take up the work sooner, please create a ticket first so that others know.
Cheers, Marc
Op woensdag 27 september 2017 22:30:33 UTC+2 schreef Joseph Obernberger:
Thank you Marc. That runs on my cluster, but takes a very long
time. If I try it on a larger graph, the YARN jobs run out of
heap. Right now I'm giving them 10G each.
On a small graph, I can run it OK, and I can run the
BulkDumperVertexProgram as well. What I can't do, when I run with
SparkGraphComputer, is look at the results.
After running:
result =
graph.compute(SparkGraphComputer).program(PageRankVertexProgram.build().create()).submit().get()
I can do a result.memory().runtime, which returns a number (in my
case 609821).
I then do:
g = result.graph().traversal(computer(SparkGraphComputer))
Unfortunately, any command with g, gives the same error - for
example:
g.V().valueMap() returns:
java.io.IOException: No input paths specified in job
Since this is a small graph, if I run it without
SparkGraphComputer, those commands on g work fine, such as:
g.V(id).valueMap('gremlin.pageRankVertexProgram.pageRank')
Trying to find any method to run PageRank on a very large graph
that is stored in JanusGraph. Thanks! Anything you would like me
to try?
-Joe
On 9/27/2017 12:04 PM, HadoopMarc
wrote:
Hi Joe,
My thoughts were more like:
graph =
GraphFactory.open('conf/hadoop-graph/read-hbase-spark-yarn.properties')
result=graph.compute(SparkGraphComputer).program(PageRankVertexProgram.build().create()).submit().get()
along the lines of "Exporting with
BulkDumperVertexProgram" in http://tinkerpop.apache.org/docs/3.2.3/reference/#sparkgraphcomputer
I am curious whether it works!
Marc
Op woensdag 27 september 2017 15:06:19 UTC+2 schreef Joseph
Obernberger:
Hi Marc - not sure I understand. I tried this:
gremlin>
g=graph.traversal()
==>graphtraversalsource[standardjanusgraph[hbase:[10.22.5.63:2181,
10.22.5.64:2181,
10.22.5.65:2181]], standard]
gremlin>
result=graph.compute().program(PageRankVertexProgram.build().create()).submit().get()
Is that what you mean? That does not work on very large
graphs. Even on a small graph (about 9 million nodes), it
took 8 hours to complete, and uses only one machine to do
the work. I'm looking for methods to calculate values on
very large graphs. Any ideas?
Thank you!
-Joe
On 9/26/2017 3:40 PM, HadoopMarc wrote:
Hi Joe,
No, not exactly, because the TinkerPop recipe points at
spark-submit as the source of most of the version
conflicts. Spark-submit is just a big wrapper around the
Spark launch API that sets the environment but does not
do that in an application-friendly way. I would first
try from the gremlin console for which the recipe was
written. Doing the OLAP pagerank in a java project
without spark-submit will require some effort to get the
classpath right.
HTH, Marc
Op dinsdag 26 september 2017 00:46:26 UTC+2 schreef
Joseph Obernberger:
Thank you Marc. I assume this would be java code
that would be executed via spark-submit?
-Joe
On 9/25/2017 3:21 PM, HadoopMarc wrote:
Hi Joe,
Maybe a suggestion after all. I believe you ran
the PageRankVertexProgram directly on the
JanusGraph instance, but it should also be
possible to run it on a HadoopGraph with
compute(SparkGraphComputer) via JanusGraph's
HBaseInputFormat. That would at least
parallelize the table scan to the number of
HBase regions. In my previous answer I assumed
you did that!
Cheers, Marc
Op maandag 25 september 2017 17:24:55 UTC+2
schreef Joseph Obernberger:
It reminds me of that one too! At
present, I'm locked in with HBase, so I
can't make the switch to Cassandra very
easily. I did try:
result = graph.compute().program(PageRankVertexProgram.build().create()).submit().get()
It took a little over 8 hours to run, but
did complete once I adjusted the
hbase.client.scanner.timeout.period
to something very long. Interestingly, I
had to modify that in the included jar
file, not in the file in /etc/hbase/conf.
Would really like to get this time to run
way down, but not sure what other method
to try.
-Joe
On 9/22/2017 1:05 PM, HadoopMarc wrote:
Hi Joe,
This question reminds me to an
earlier discussion we had on the
performance of OLAP traversals for
janusgraph-hbase. My conclusion there
that janusgraph-hbase needs a better
HbaseInputFormat that delivers more
partitions than one partition per HBase
region. I guess Pagerank suffers from
that in the same way. Do you maybe have
the option to use Cassandra, which has a
configurable cassandra.inpit.split.size
? I did not try this myself.
HTH, Marc
Op vrijdag 22 september 2017 15:41:12
UTC+2 schreef Joseph Obernberger:
Hi All -
I've been experimenting with
SparkGraphComputer, and have it
working, but I'm having performance
issues. What is the best way to run
PageRank against a very large graph
stored inside of JanusGraph?
Thank you!
-Joe
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