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Jason Rutherglen commented on SOLR-1301: ---------------------------------------- I think we can parallelize the indexing in SolrRecordWriter? Meaning multiple threads add docs to Solr? Most machines will have multiple cores and only one task is running per machine at a time? > Solr + Hadoop > ------------- > > Key: SOLR-1301 > URL: https://issues.apache.org/jira/browse/SOLR-1301 > Project: Solr > Issue Type: Improvement > Affects Versions: 1.4 > Reporter: Andrzej Bialecki > Attachments: hadoop-0.19.1-core.jar, hadoop.patch, solr.zip > > > This patch contains a contrib module that provides distributed indexing > (using Hadoop) to Solr EmbeddedSolrServer. The idea behind this module is > twofold: > * provide an API that is familiar to Hadoop developers, i.e. that of > OutputFormat > * avoid unnecessary export and (de)serialization of data maintained on HDFS. > SolrOutputFormat consumes data produced by reduce tasks directly, without > storing it in intermediate files. Furthermore, by using an > EmbeddedSolrServer, the indexing task is split into as many parts as there > are reducers, and the data to be indexed is not sent over the network. > Design > ---------- > Key/value pairs produced by reduce tasks are passed to SolrOutputFormat, > which in turn uses SolrRecordWriter to write this data. SolrRecordWriter > instantiates an EmbeddedSolrServer, and it also instantiates an > implementation of SolrDocumentConverter, which is responsible for turning > Hadoop (key, value) into a SolrInputDocument. This data is then added to a > batch, which is periodically submitted to EmbeddedSolrServer. When reduce > task completes, and the OutputFormat is closed, SolrRecordWriter calls > commit() and optimize() on the EmbeddedSolrServer. > The API provides facilities to specify an arbitrary existing solr.home > directory, from which the conf/ and lib/ files will be taken. > This process results in the creation of as many partial Solr home directories > as there were reduce tasks. The output shards are placed in the output > directory on the default filesystem (e.g. HDFS). Such part-NNNNN directories > can be used to run N shard servers. Additionally, users can specify the > number of reduce tasks, in particular 1 reduce task, in which case the output > will consist of a single shard. > An example application is provided that processes large CSV files and uses > this API. It uses a custom CSV processing to avoid (de)serialization overhead. > This patch relies on hadoop-core-0.19.1.jar - I attached the jar to this > issue, you should put it in contrib/hadoop/lib. > Note: the development of this patch was sponsored by an anonymous contributor > and approved for release under Apache License. -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.