为Spark集群和Cassandra设置和配置JanusGraph

Question

我正在单机上运行JanusGraph (0.1.0) 和 Spark (1.6.1) 。我的配置如这里所述。在使用SparkGraphComputer访问图形时，它总是为空的。我在日志文件中找不到任何错误，只是一个空图。

是否有人使用JanusGraph和Spark并分享他的配置和属性?

使用JanusGraph时，我得到了预期的输出:

gremlin> graph=JanusGraphFactory.open('conf/test.properties')
==>standardjanusgraph[cassandrathrift:[127.0.0.1]]
gremlin> g=graph.traversal()
==>graphtraversalsource[standardjanusgraph[cassandrathrift:[127.0.0.1]], standard]
gremlin> g.V().count()
14:26:10 WARN  org.janusgraph.graphdb.transaction.StandardJanusGraphTx  - Query requires iterating over all vertices [()]. For better performance, use indexes
==>1000001
gremlin>

使用将HadoopGraph与Spark作为GraphComputer，图形为空：

gremlin> graph=GraphFactory.open('conf/test.properties')
==>hadoopgraph[cassandrainputformat->gryooutputformat]
gremlin> g=graph.traversal().withComputer(SparkGraphComputer)
==>graphtraversalsource[hadoopgraph[cassandrainputformat->gryooutputformat], sparkgraphcomputer]
gremlin> g.V().count()
            ==>0==============================================>   (14 + 1) / 15]

我的conf/test.properties文件：

#
# Hadoop Graph Configuration
#
gremlin.graph=org.apache.tinkerpop.gremlin.hadoop.structure.HadoopGraph
gremlin.hadoop.graphInputFormat=org.janusgraph.hadoop.formats.cassandra.CassandraInputFormat
gremlin.hadoop.graphOutputFormat=org.apache.tinkerpop.gremlin.hadoop.structure.io.gryo.GryoOutputFormat
gremlin.hadoop.memoryOutputFormat=org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat
gremlin.hadoop.memoryOutputFormat=org.apache.tinkerpop.gremlin.hadoop.structure.io.gryo.GryoOutputFormat

gremlin.hadoop.deriveMemory=false
gremlin.hadoop.jarsInDistributedCache=true
gremlin.hadoop.inputLocation=none
gremlin.hadoop.outputLocation=output

#
# Titan Cassandra InputFormat configuration
#
janusgraphmr.ioformat.conf.storage.backend=cassandrathrift
janusgraphmr.ioformat.conf.storage.hostname=127.0.0.1
janusgraphmr.ioformat.conf.storage.keyspace=janusgraph
storage.backend=cassandrathrift
storage.hostname=127.0.0.1
storage.keyspace=janusgraph

#
# Apache Cassandra InputFormat configuration
#
cassandra.input.partitioner.class=org.apache.cassandra.dht.Murmur3Partitioner
cassandra.input.keyspace=janusgraph
cassandra.input.predicate=0c00020b0001000000000b000200000000020003000800047fffffff0000
cassandra.input.columnfamily=edgestore
cassandra.range.batch.size=2147483647

#
# SparkGraphComputer Configuration
#
spark.master=spark://127.0.0.1:7077
spark.serializer=org.apache.spark.serializer.KryoSerializer
spark.executor.memory=100g

gremlin.spark.persistContext=true
gremlin.hadoop.defaultGraphComputer=org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer

根据这里的描述，HDFS似乎已经正确配置了：

gremlin> hdfs
==>storage[DFS[DFSClient[clientName=DFSClient_NONMAPREDUCE_178390072_1, ugi=cassandra (auth:SIMPLE)]]]

- Felix Hill

Answer 1

尝试修复以下属性：

janusgraphmr.ioformat.conf.storage.keyspace=janusgraph
storage.keyspace=janusgraph

替换为：

janusgraphmr.ioformat.conf.storage.cassandra.keyspace=janusgraph
storage.cassandra.keyspace=janusgraph

默认的键空间名称是janusgraph，所以尽管在属性名称上存在错误，我认为除非您使用不同的键空间名称加载数据，否则您不会观察到该问题。

后面的属性在配置参考中有描述。此外，请留意这个未解决的问题，以改进Hadoop-Graph使用文档。

- Jason Plurad