问题
I have been playing around with using graphs to analyze big data. Its been working great and really fun but I'm wondering what to do as the data gets bigger and bigger?
Let me know if there's any other solution but I thought of trying Hbase because it scales horizontally and I can get hadoop to run analytics on the graph(most of my code is already written in java), but I'm unsure how to structure a graph on a nosql database? I know each node can be an entry in the database but I'm not sure how to model edges and add properties to them(like name of nodes, attributes, pagerank, weights on edges,etc..).
Seeing how hbase/hadoop is modeled after big tables and map reduce I suspect there is a way to do this but not sure how. Any suggestions?
Also, does this make sense what I'm trying to do? or is it there better solutions for big data graphs?
回答1:
You can store an adjacency list in HBase/Accumulo in a column oriented fashion. I'm more familiar with Accumulo (HBase terminology might be slightly different) so you might use a schema similar to:
SrcNode(RowKey) EdgeType(CF):DestNode(CFQ) Edge/Node Properties(Value)
Where CF=ColumnFamily and CFQ=ColumnFamilyQualifier
You might also store node/vertex properties as separate rows using something like:
Node(RowKey) PropertyType(CF):PropertyValue(CFQ) PropertyValue(Value)
The PropertyValue could be either in the CFQ or the Value
From a graph processing perspective as mentioned by @Arnon Rotem-Gal-Oz you could look at Apache Giraph which is an implementation of Google Pregel. Pregel is the method Google use for large graph processing.
Using HBase/Accumulo as input to giraph has been submitted recently (7 Mar 2012) as a new feature request to Giraph: HBase/Accumulo Input and Output formats (GIRAPH-153)
回答2:
You can store the graph in HBase as adjacency list so for example, each raw would have columns for general properties (name, pagerank etc.) and a list of keys of adjacent nodes (if it a directed graph than just the nodes you can get to from this node or an additional column with the direction of each)
Take a look at apache Giraph (you can also read a little more about it here) while this isn't about HBase it is about handling graphs in Hadoop. Also you may want to look at Hadoop 0.23 (and up) as the YARN engine (aka map/reduce2) is more open to non-map/reduce algorithms
回答3:
I would not use HBase in the way "Binary Nerd" recommended it as HBase does not perform very well when handling multiple column families.
Best performance is achieved with a single column family (a second one should only be used if you very often only access the content of one column family and the data stored in the other column family is very large)
回答4:
There are graph databases build on top of HBase you could try and/or study.
Apache S2Graph provides REST API for storing, querying the graph data represented by edge and vertices. There you can find a presentation, where the construction of row/column keys is explained. Analysis of operations' performance that influenced or is influenced by the design are also given.
Titan can use other storage backends besides HBase, and has integration with analytics frameworks. It is also designed with big data sets in mind.
来源：https://stackoverflow.com/questions/9865738/is-it-possible-to-store-graphs-hbase-if-so-how-do-you-model-the-database-to-sup