Avery, I think I didn't make myself very clear in the first email. I have already wrote a range based partitioner, and it works. But exactly as you said, the vertices shipped is pretty much the same as the hash partitioner. Actually the vertices loading time is a bit slower than hash partitioner, because it takes a bit more time to check for the partition id for each vertex. I did observe the reduction of the # of messages in the giraph job.
Now, what I want to do is to reduce the loading time. I have preprocessed the input graph so that data is divided into n files (n is the number of workers I want to use for my giraph job later), each file contains a few range-based partitions. I know the partition ranges and which file each partition belongs to before I run my giraph job. I want a new partitioner so that each worker will read local data without checking for partitionID and use the ranges of the local data to register as the partitions it is responsible for. This way the loading phase doesn't need to check for partitionid for each vertex and it doesn't need to ship vertices to other workers either. I understand this will be a special paritioner only used when the input data is very well organized. My question is how I can achieve this. Yuanyuan From: Avery Ching <[email protected]> To: [email protected] Cc: Yuanyuan Tian/Almaden/IBM@IBMUS Date: 05/25/2012 11:10 AM Subject: Re: Question about range partitioner and data locality Writing a range based partitioner is for potentially reducing the number of messages between workers (i.e. reverse lexical ordering of urls for page rank). Without changes to the input splits loading, the average number vertices shipped during the input superstep will be the same as the using the hash partitioner. Is this what you are trying to achieve? Avery On 5/25/12 10:57 AM, Yuanyuan Tian wrote: I am not suggesting to change the current range partitioner, as it is designed for a general case. I want to write a special partitioner based on the existing range partitioner to achieve what I want to do in this special situation, but I don't know how. Yuanyuan -----Avery Ching <[email protected]> wrote: ----- To: [email protected] From: Avery Ching <[email protected]> Date: 05/24/2012 11:59PM Subject: Re: Question about range partitioner and data locality You are definitely right that the old version of Giraph supported ranges pretty well for loading, but could not support hash based distribution (much better for memory distribution across workers). It also made a lot of assumptions (the data within each split was in a unique range and sorted). Unless we make these type of assumptions, it would be pretty hard to do. One way might be to have all the workers examine each input split, and each input split would provide on information as to its range. If the worker matches that range, it would attempt to load some or all of the vertices in that split. Otherwise, it would try the next split. Any other ideas? Avery On 5/23/12 5:36 PM, Yuanyuan Tian wrote: Hi, I want to use better partitions of input graph for my algorithm running on Giraph. So, I partitioned my input graph and re-labeled the vertex ids so that vertex ids of the same partition are in a consecutive range. I also reorganized the input file so that the vertices in the same range are together. I used the range partitioner for the Giraph job to utilize the better partitions. However, the vertex loader still looks for the partition id of each vertex and ship it to the worker that owns the partition. On the other hand, I have already prepared my data in a nice way, in the ideal case, I can just keep all the vertices of an inputsplit local to the corresponding worker. Is there an easy way to do this? I know that in the very old version of giraph, giraph doesn't have a partitioner. The users have to prepare the partitions. I essentially want to do a similar thing in the current version of giraph. Please give me a pointer or two on how to do this. Thanks, Yuanyuan
