HBaseMapReduceIndexerTool is a MapReduce batch job driver that takes input data from an HBase table and creates Solr index shards and writes the indexes into HDFS, in a flexible, scalable, and fault-tolerant manner. It also supports merging the output shards into a set of live customer-facing Solr servers in SolrCloud.
$ hadoop jar /usr/lib/hbase-solr/tools/hbase-indexer-mr-*-job.jar --help usage: hadoop [GenericOptions]... jar hbase-indexer-mr-*-job.jar [--hbase-indexer-zk STRING] [--hbase-indexer-name STRING] [--hbase-indexer-file FILE] [--hbase-table-name STRING] [--hbase-start-row BINARYSTRING] [--hbase-end-row BINARYSTRING] [--hbase-start-time STRING] [--hbase-end-time STRING] [--hbase-timestamp-format STRING] [--zk-host STRING] [--go-live] [--collection STRING] [--go-live-threads INTEGER] [--help] [--output-dir HDFS_URI] [--overwrite-output-dir] [--morphline-file FILE] [--morphline-id STRING] [--update-conflict-resolver FQCN] [--reducers INTEGER] [--max-segments INTEGER] [--fair-scheduler-pool STRING] [--dry-run] [--log4j FILE] [--verbose] [--show-non-solr-cloud] MapReduce batch job driver that takes input data from an HBase table and creates Solr index shards and writes the indexes into HDFS, in a flexible, scalable, and fault-tolerant manner. It also supports merging the output shards into a set of live customer-facing Solr servers in SolrCloud. Optionally, documents can be sent directly from the mapper tasks to SolrCloud, which is a much less scalable approach but enables updating existing documents in SolrCloud. The program proceeds in one or multiple consecutive MapReduce-based phases, as follows: 1) Mapper phase: This (parallel) phase scans over the input HBase table, extracts the relevant content, and transforms it into SolrInputDocuments. If run as a mapper-only job, this phase also writes the SolrInputDocuments directly to a live SolrCloud cluster. The conversion from HBase records into Solr documents is performed via a hbase-indexer configuration and typically based on a morphline. 2) Reducer phase: This (parallel) phase loads the mapper's SolrInputDocuments into one EmbeddedSolrServer per reducer. Each such reducer and Solr server can be seen as a (micro) shard. The Solr servers store their data in HDFS. 3) Mapper-only merge phase: This (parallel) phase merges the set of reducer shards into the number of Solr shards expected by the user, using a mapper-only job. This phase is omitted if the number of shards is already equal to the number of shards expected by the user 4) Go-live phase: This optional (parallel) phase merges the output shards of the previous phase into a set of live customer-facing Solr servers in SolrCloud. If this phase is omitted you can expecitly point each Solr server to one of the HDFS output shard directories Fault Tolerance: Mapper and reducer task attempts are retried on failure per the standard MapReduce semantics. On program startup all data in the -- output-dir is deleted if that output directory already exists and -- overwrite-output-dir is specified. This means that if the whole job fails you can retry simply by rerunning the program again using the same arguments. HBase Indexer parameters: Parameters for specifying the HBase indexer definition and/or where it should be loaded from. --hbase-indexer-zk STRING The address of the ZooKeeper ensemble from which to fetch the indexer definition named --hbase- indexer-name. Format is: a list of comma separated host:port pairs, each corresponding to a zk server. Example: '127.0.0.1:2181,127.0.0.1: 2182,127.0.0.1:2183' --hbase-indexer-name STRING The name of the indexer configuration to fetch from the ZooKeeper ensemble specified with -- hbase-indexer-zk. Example: myIndexer --hbase-indexer-file FILE Relative or absolute path to a local HBase indexer XML configuration file. If supplied, this overrides --hbase-indexer-zk and --hbase-indexer- name. Example: /path/to/morphline-hbase-mapper.xml HBase scan parameters: Parameters for specifying what data is included while reading from HBase. --hbase-table-name STRING Optional name of the HBase table containing the records to be indexed. If supplied, this overrides the value from the --hbase-indexer-* options. Example: myTable --hbase-start-row BINARYSTRING Binary string representation of start row from which to start indexing (inclusive). The format of the supplied row key should use two-digit hex values prefixed by \x for non-ascii characters (e. g. 'row\x00'). The semantics of this argument are the same as those for the HBase Scan#setStartRow method. The default is to include the first row of the table. Example: AAAA --hbase-end-row BINARYSTRING Binary string representation of end row prefix at which to stop indexing (exclusive). See the description of --hbase-start-row for more information. The default is to include the last row of the table. Example: CCCC --hbase-start-time STRING Earliest timestamp (inclusive) in time range of HBase cells to be included for indexing. The default is to include all cells. Example: 0 --hbase-end-time STRING Latest timestamp (exclusive) of HBase cells to be included for indexing. The default is to include all cells. Example: 123456789 --hbase-timestamp-format STRING Timestamp format to be used to interpret --hbase- start-time and --hbase-end-time. This is a java. text.SimpleDateFormat compliant format (see http: //docs.oracle. com/javase/6/docs/api/java/text/SimpleDateFormat. html). If this parameter is omitted then the timestamps are interpreted as number of milliseconds since the standard epoch (Unix time). Example: yyyy-MM-dd'T'HH:mm:ss.SSSZ Solr cluster arguments: Arguments that provide information about your Solr cluster. --zk-host STRING The address of a ZooKeeper ensemble being used by a SolrCloud cluster. This ZooKeeper ensemble will be examined to determine the number of output shards to create as well as the Solr URLs to merge the output shards into when using the --go- live option. Requires that you also pass the -- collection to merge the shards into. The --zk-host option implements the same partitioning semantics as the standard SolrCloud Near-Real-Time (NRT) API. This enables to mix batch updates from MapReduce ingestion with updates from standard Solr NRT ingestion on the same SolrCloud cluster, using identical unique document keys. Format is: a list of comma separated host:port pairs, each corresponding to a zk server. Example: '127.0.0.1:2181,127.0.0.1:2182,127.0.0.1: 2183' If the optional chroot suffix is used the example would look like: '127.0.0.1:2181/solr, 127.0.0.1:2182/solr,127.0.0.1:2183/solr' where the client would be rooted at '/solr' and all paths would be relative to this root - i.e. getting/setting/etc... '/foo/bar' would result in operations being run on '/solr/foo/bar' (from the server perspective). Go live arguments: Arguments for merging the shards that are built into a live Solr cluster. Also see the Cluster arguments. --go-live Allows you to optionally merge the final index shards into a live Solr cluster after they are built. You can pass the ZooKeeper address with -- zk-host and the relevant cluster information will be auto detected. (default: false) --collection STRING The SolrCloud collection to merge shards into when using --go-live and --zk-host. Example: collection1 --go-live-threads INTEGER Tuning knob that indicates the maximum number of live merges to run in parallel at one time. (default: 1000) Optional arguments: --help, -help, -h Show this help message and exit --output-dir HDFS_URI HDFS directory to write Solr indexes to. Inside there one output directory per shard will be generated. Example: hdfs://c2202.mycompany. com/user/$USER/test --overwrite-output-dir Overwrite the directory specified by --output-dir if it already exists. Using this parameter will result in the output directory being recursively deleted at job startup. (default: false) --morphline-file FILE Relative or absolute path to a local config file that contains one or more morphlines. The file must be UTF-8 encoded. The file will be uploaded to each MR task. If supplied, this overrides the value from the --hbase-indexer-* options. Example: /path/to/morphlines.conf --morphline-id STRING The identifier of the morphline that shall be executed within the morphline config file, e.g. specified by --morphline-file. If the --morphline- id option is ommitted the first (i.e. top-most) morphline within the config file is used. If supplied, this overrides the value from the -- hbase-indexer-* options. Example: morphline1 --update-conflict-resolver FQCN Fully qualified class name of a Java class that implements the UpdateConflictResolver interface. This enables deduplication and ordering of a series of document updates for the same unique document key. For example, a MapReduce batch job might index multiple files in the same job where some of the files contain old and new versions of the very same document, using the same unique document key. Typically, implementations of this interface forbid collisions by throwing an exception, or ignore all but the most recent document version, or, in the general case, order colliding updates ascending from least recent to most recent (partial) update. The caller of this interface (i. e. the Hadoop Reducer) will then apply the updates to Solr in the order returned by the orderUpdates() method. The default RetainMostRecentUpdateConflictResolver implementation ignores all but the most recent document version, based on a configurable numeric Solr field, which defaults to the file_last_modified timestamp (default: org.apache. solr.hadoop.dedup. RetainMostRecentUpdateConflictResolver) --reducers INTEGER Tuning knob that indicates the number of reducers to index into. 0 indicates that no reducers should be used, and documents should be sent directly from the mapper tasks to live Solr servers. -1 indicates use all reduce slots available on the cluster. -2 indicates use one reducer per output shard, which disables the mtree merge MR algorithm. The mtree merge MR algorithm improves scalability by spreading load (in particular CPU load) among a number of parallel reducers that can be much larger than the number of solr shards expected by the user. It can be seen as an extension of concurrent lucene merges and tiered lucene merges to the clustered case. The subsequent mapper-only phase merges the output of said large number of reducers to the number of shards expected by the user, again by utilizing more available parallelism on the cluster. (default: -1) --max-segments INTEGER Tuning knob that indicates the maximum number of segments to be contained on output in the index of each reducer shard. After a reducer has built its output index it applies a merge policy to merge segments until there are <= maxSegments lucene segments left in this index. Merging segments involves reading and rewriting all data in all these segment files, potentially multiple times, which is very I/O intensive and time consuming. However, an index with fewer segments can later be merged faster, and it can later be queried faster once deployed to a live Solr serving shard. Set maxSegments to 1 to optimize the index for low query latency. In a nutshell, a small maxSegments value trades indexing latency for subsequently improved query latency. This can be a reasonable trade-off for batch indexing systems. (default: 1) --fair-scheduler-pool STRING Optional tuning knob that indicates the name of the fair scheduler pool to submit jobs to. The Fair Scheduler is a pluggable MapReduce scheduler that provides a way to share large clusters. Fair scheduling is a method of assigning resources to jobs such that all jobs get, on average, an equal share of resources over time. When there is a single job running, that job uses the entire cluster. When other jobs are submitted, tasks slots that free up are assigned to the new jobs, so that each job gets roughly the same amount of CPU time. Unlike the default Hadoop scheduler, which forms a queue of jobs, this lets short jobs finish in reasonable time while not starving long jobs. It is also an easy way to share a cluster between multiple of users. Fair sharing can also work with job priorities - the priorities are used as weights to determine the fraction of total compute time that each job gets. --dry-run Run in local mode and print documents to stdout instead of loading them into Solr. This executes the morphline in the client process (without submitting a job to MR) for quicker turnaround during early trial & debug sessions. (default: false) --log4j FILE Relative or absolute path to a log4j.properties config file on the local file system. This file will be uploaded to each MR task. Example: /path/to/log4j.properties --verbose, -v Turn on verbose output. (default: false) Generic options supported are --conf <configuration file> specify an application configuration file -D <property=value> use value for given property --fs <local|namenode:port> specify a namenode --jt <local|jobtracker:port> specify a job tracker --files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster --libjars <comma separated list of jars> specify comma separated jar files to include in the classpath. --archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines. The general command line syntax is bin/hadoop command [genericOptions] [commandOptions] Examples: # (Re)index a table in GoLive mode based on a local indexer config file hadoop --config /etc/hadoop/conf jar hbase-indexer-mr-*-job.jar --conf \ /etc/hbase/conf/hbase-site.xml -D 'mapred.child.java.opts=-Xmx500m' \ --hbase-indexer-file indexer.xml --zk-host 127.0.0.1/solr --collection \ collection1 --go-live --log4j src/test/resources/log4j.properties # (Re)index a table in GoLive mode using a local morphline-based indexer config file hadoop --config /etc/hadoop/conf jar hbase-indexer-mr-*-job.jar --conf \ /etc/hbase/conf/hbase-site.xml -D 'mapred.child.java.opts=-Xmx500m' \ --hbase-indexer-file src/test/resources/morphline_indexer_without_zk.xml \ --zk-host 127.0.0.1/solr --collection collection1 --go-live --morphline-file \ src/test/resources/morphlines.conf --output-dir \ hdfs://c2202.mycompany.com/user/$USER/test --overwrite-output-dir --log4j \ src/test/resources/log4j.properties # (Re)index a table in GoLive mode hadoop --config /etc/hadoop/conf jar hbase-indexer-mr-*-job.jar --conf \ /etc/hbase/conf/hbase-site.xml -D 'mapred.child.java.opts=-Xmx500m' \ --hbase-indexer-file indexer.xml --zk-host 127.0.0.1/solr --collection \ collection1 --go-live --log4j src/test/resources/log4j.properties # (Re)index a table with direct writes to SolrCloud hadoop --config /etc/hadoop/conf jar hbase-indexer-mr-*-job.jar --conf \ /etc/hbase/conf/hbase-site.xml -D 'mapred.child.java.opts=-Xmx500m' \ --hbase-indexer-file indexer.xml --zk-host 127.0.0.1/solr --collection \ collection1 --reducers 0 --log4j src/test/resources/log4j.properties # (Re)index a table based on a indexer config stored in ZK hadoop --config /etc/hadoop/conf jar hbase-indexer-mr-*-job.jar --conf \ /etc/hbase/conf/hbase-site.xml -D 'mapred.child.java.opts=-Xmx500m' \ --hbase-indexer-zk zk01 --hbase-indexer-name docindexer --go-live --log4j \ src/test/resources/log4j.properties