使用MR方案脚本访问HBase数据、Compact+Split问题-参数配置

Conpaction做的是数据文件合并，过大时Split，当一个region split 文件过多时还可以用 Merge去合并文件避免Conpact、split (特别和hive整合时) 跟下面四个参数都有关//--------------------------------------------------------------------hbase.hregion.memstore.flush.size --- 跟split相关，达到这个大小就写入HBase，调大避免产生过多的storeFilehbase.hregion.max.fileze          (table_att => MAX_FILESIZE) 设置得非常大就可以避免自动splithbase.hstore.compactionThreshold  阈值(hstore的文件个数积累到什么数（8乘以flush.size）时触发Conpaction)，如置8：超过8个文件就开始split，跟flush.size相关hbase.hregion.majorcompaction     majorcompaction间隔时间设置，删除过期的数据MapReduce方案//--------------------------------相关请看上篇文章IndexBuilder：利用MR的方式构建Index 优点：可以并发批量构建Index 缺点：当对hbase插入一条数据时，不能实时构建Index    ›坑！。。。        –老要想着设scan cache        –block cache开还是不开        –bloom filter有用不        –莫名其妙的job就挂了！解决：使用MapReduce框架访问HBase数据时Compact、Split带来的问题//------------------------------------------------------  –region offline、mapper访问region失败  –调整参数控制 Compact、Split    •hbase.hregion.majorcompaction        –网上有说设成0就能避免compaction发生（错误的）        –删除过期的数据，硬盘空间不是立即清楚，很耗时耗资源    •hbase.hstore.compactionThreshold        –Region中文件个数多于此值，开始compact        –可能进入minor，（只做）合并较小StoreFile    •hbase.hregion.memstore.flush.size        –memstore何时写入HStore，region最大的fileSize,超过就split(会产生两个region-一个文件-自动做了compaction)    •hbase.hregion.max.filesize (table_att => MAX_FILESIZE)        –Region何时开始split    •hbase.hstore.blockingStoreFiles （灾难性的属性）        –max.filesize < flush.size * blockingStoreFiles 以保证region不会被block        -达到这个值就不能往里面写block，做了compaction之后才能继续往里面写内容  –offpeak hour  –merge脚本的使用：//-------------------------#!/bin/bashdie () {    echo >&2 "$@"    echo "usage:"    echo "       $0 check|split table_name [split_size]"  #//选择模式与用法，超过[split_size]就split    exit 1}[[ "$#" -lt 2 ]] && die "at least 2 arguments required, $# provided"COMMAND=$1TABLE=$2SIZE="${3:-1073741824}" #//读第三个默认参数1Gsplit() {    region_key=`python /home/hduser/hbase/hbase-scan.py -t hbase:meta -f "RowFilter (=, 'substring:$1')"`    echo "split '$region_key'" | hbase shell}if [ "$COMMAND" != "check" ] ; then    for region in `hadoop fs -ls /hbase/data/default/$TABLE | awk {'print $8'}`    do        [[ ${region##*/} =~ ^\. ]] && continue        [[ `hadoop fs -du -s $region | awk {'print $1'}` -gt $SIZE ]] && split ${region##*/}    done    # check after split    sleep 60fifor region in `hadoop fs -ls /hbase/data/default/$TABLE | awk {'print $8'}`do    [[ ${region##*/} =~ ^\. ]] && continue    [[ `hadoop fs -du -s $region | awk {'print $1'}` -gt $SIZE ]] && echo "${region##*/} (`hadoop fs -du -s -h $region | awk {'print $1 $2'}`) is a huge region" || echo "${region##*/} (`hadoop fs -du -s -h $region | awk {'print $1 $2'}`) is a small region"done上面的hbase-scan.py调用hbase读region在hbase:meta表里的一个key//---------------------------------------------------------import subprocessimport datetimeimport argparseimport csvimport gzipimport happybaseimport loggingdef connect_to_hbase():    return happybase.Connection('itr-hbasetest01')def main():    logging.basicConfig(format='%(asctime)s %(name)s %(levelname)s: %(message)s',level=logging.INFO)    argp = argparse.ArgumentParser(description='EventLog Reader')    argp.add_argument('-t','--table', dest='table', default='eventlog')    argp.add_argument('-p','--prefix', dest='prefix')    argp.add_argument('-f','--filter', dest='filter')    argp.add_argument('-l','--limit', dest='limit', default=10)    args = argp.parse_args()    hbase_conn = connect_to_hbase()    table = hbase_conn.table(args.table)    logging.info("scan start")    scanner = table.scan(row_prefix=args.prefix, batch_size=1000, limit=int(args.limit), filter=args.filter)    logging.info("scan done")    i = 0    for key, data in scanner:        logging.info(key)        print key        i+=1    logging.info('%s rows read in total', i)if __name__ == '__main__':    main()