为 Spark 集群和 Cassandra 设置和配置 JanusGraph

Question

我运行 JanusGraph (0.1.0) 和 Spark (1.6.1) 在一台机器上。我按照所述进行了配置。使用 SparkGraphComputer 访问 gremlin-console 上的图形时，它始终为空。我在日志文件中找不到任何错误，它只是一个空图表。

是否有人将 JanusGraph 与 Spark 一起使用并且可以分享他的配置和属性？

使用 JanusGraph，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>

使用带有 Spark 的 HadoopGraph 作为 GraphComputer，图为空：

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.属性：

#
# 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

HDFS 似乎配置正确 here:

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

Answer 1

尝试修复这些属性：

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

替换为：

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

默认键空间名称是 janusgraph，因此尽管属性名称存在错误，但我认为您不会发现该问题，除非您使用不同的键空间名称加载数据.

后者属性在 Configuration Reference. Also, keep an eye on this open issue 中描述，以改进 Hadoop-Graph 使用的文档。

为 Spark 集群和 Cassandra 设置和配置 JanusGraph

Setup and configuration of JanusGraph for a Spark cluster and Cassandra

hadoop

apache-spark

cassandra

titan

janusgraph