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Hbase Filter过滤器查询详解

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过滤器查询

引言:过滤器的类型很多,但是可以分为两大类——比较过滤器专用过滤器

过滤器的作用是在服务端判断数据是否满足条件,然后只将满足条件的数据返回给客户端;

 

hbase过滤器的比较运算符:

LESS  <

LESS_OR_EQUAL <=

EQUAL =

NOT_EQUAL <>

GREATER_OR_EQUAL >=

GREATER >

NO_OP 排除所有

 

Hbase过滤器的比较器(指定比较机制):

BinaryComparator  按字节索引顺序比较指定字节数组,采用Bytes.compareTo(byte[])

BinaryPrefixComparator 跟前面相同,只是比较左端的数据是否相同

NullComparator 判断给定的是否为空

BitComparator 按位比较

RegexStringComparator 提供一个正则的比较器,仅支持 EQUAL 和非EQUAL

SubstringComparator 判断提供的子串是否出现在value中。

 

Hbase的过滤器分类

 

  • 比较过滤器

1.1  行键过滤器RowFilter

Filter filter1 = new RowFilter(CompareOp.LESS_OR_EQUAL, new BinaryComparator(Bytes.toBytes("row-22"))); 

scan.setFilter(filter1); 

 

1.2  列族过滤器FamilyFilter

Filter filter1 = new FamilyFilter(CompareFilter.CompareOp.LESS, new BinaryComparator(Bytes.toBytes("colfam3")));

scan.setFilter(filter1); 

 

1.3 列过滤器QualifierFilter

filter = new QualifierFilter(CompareFilter.CompareOp.LESS_OR_EQUAL, new BinaryComparator(Bytes.toBytes("col-2")));

scan.setFilter(filter1);

 

1.4 值过滤器 ValueFilter 

Filter filter = new ValueFilter(CompareFilter.CompareOp.EQUAL, new SubstringComparator(".4") ); 

scan.setFilter(filter1); 

 

 

  • 专用过滤器

2.1 单列值过滤器 SingleColumnValueFilter  ----会返回满足条件的整行

SingleColumnValueFilter filter = new SingleColumnValueFilter( 

    Bytes.toBytes("colfam1"), 

    Bytes.toBytes("col-5"), 

    CompareFilter.CompareOp.NOT_EQUAL, 

    new SubstringComparator("val-5")); 

filter.setFilterIfMissing(true);  //如果不设置为true,则那些不包含指定column的行也会返回

scan.setFilter(filter1); 

 

2.2  SingleColumnValueExcludeFilter

与上相反

 

2.3 前缀过滤器 PrefixFilter----针对行键

Filter filter = new PrefixFilter(Bytes.toBytes("row1")); 

scan.setFilter(filter1); 

 

2.4 列前缀过滤器 ColumnPrefixFilter

Filter filter = new ColumnPrefixFilter(Bytes.toBytes("qual2")); 

scan.setFilter(filter1); 

 

2.4分页过滤器 PageFilter

       public static void main(String[] args) throws Exception {

              Configuration conf = HBaseConfiguration.create();

              conf.set("hbase.zookeeper.quorum", "spark01:2181,spark02:2181,spark03:2181");

             

              String tableName = "testfilter"; 

              String cfName = "f1"; 

              final byte[] POSTFIX = new byte[] { 0x00 }; 

              HTable table = new HTable(conf, tableName); 

              Filter filter = new PageFilter(3); 

              byte[] lastRow = null; 

              int totalRows = 0; 

              while (true) { 

                  Scan scan = new Scan(); 

                  scan.setFilter(filter); 

                  if(lastRow != null){ 

                //注意这里添加了POSTFIX操作,用来重置扫描边界 

                      byte[] startRow = Bytes.add(lastRow,POSTFIX); 

                      scan.setStartRow(startRow); 

                  } 

                  ResultScanner scanner = table.getScanner(scan); 

                  int localRows = 0; 

                  Result result; 

                  while((result = scanner.next()) != null){ 

                      System.out.println(localRows++ + ":" + result); 

                      totalRows ++; 

                      lastRow = result.getRow(); 

                  } 

                  scanner.close(); 

                  if(localRows == 0) break; 

              } 

              System.out.println("total rows:" + totalRows); 

       }

 

 

 

 

 

 

       /**

     * 多种过滤条件的使用方法

        * @throws Exception

        */

       @Test

       public void testScan() throws Exception{

              HTable table = new HTable(conf, "person_info".getBytes());

              Scan scan = new Scan(Bytes.toBytes("person_rk_bj_zhang_000001"), Bytes.toBytes("person_rk_bj_zhang_000002"));

             

        //前缀过滤器----针对行键

              Filter filter = new PrefixFilter(Bytes.toBytes("rk"));

             

        //行过滤器  ---针对行键

              ByteArrayComparable rowComparator = new BinaryComparator(Bytes.toBytes("person_rk_bj_zhang_000001"));

              RowFilter rf = new RowFilter(CompareOp.LESS_OR_EQUAL, rowComparator);

             

              /**

         * 假设rowkey格式为:创建日期_发布日期_ID_TITLE

         * 目标:查找  发布日期  为  2014-12-21  的数据

         * sc.textFile("path").flatMap(line=>line.split("\t")).map(x=>(x,1)).reduceByKey(_+_).map((_(2),_(1))).sortByKey().map((_(2),_(1))).saveAsTextFile("")

         *

         *

         */

        rf = new RowFilter(CompareOp.EQUAL , new SubstringComparator("_2014-12-21_"));

             

             

        //单值过滤器1完整匹配字节数组

              new SingleColumnValueFilter("base_info".getBytes(), "name".getBytes(), CompareOp.EQUAL, "zhangsan".getBytes());

        //单值过滤器2 匹配正则表达式

              ByteArrayComparable comparator = new RegexStringComparator("zhang.");

              new SingleColumnValueFilter("info".getBytes(), "NAME".getBytes(), CompareOp.EQUAL, comparator);

 

        //单值过滤器3匹配是否包含子串,大小写不敏感

              comparator = new SubstringComparator("wu");

              new SingleColumnValueFilter("info".getBytes(), "NAME".getBytes(), CompareOp.EQUAL, comparator);

 

        //键值对元数据过滤-----family过滤----字节数组完整匹配

        FamilyFilter ff = new FamilyFilter(

                CompareOp.EQUAL ,

                new BinaryComparator(Bytes.toBytes("base_info"))   //表中不存在inf列族,过滤结果为空

                );

        //键值对元数据过滤-----family过滤----字节数组前缀匹配

        ff = new FamilyFilter(

                CompareOp.EQUAL ,

                new BinaryPrefixComparator(Bytes.toBytes("inf"))   //表中存在以inf打头的列族info,过滤结果为该列族所有行

                );

       

       //键值对元数据过滤-----qualifier过滤----字节数组完整匹配

       

        filter = new QualifierFilter(

                CompareOp.EQUAL ,

                new BinaryComparator(Bytes.toBytes("na"))   //表中不存在na列,过滤结果为空

                );

        filter = new QualifierFilter(

                CompareOp.EQUAL ,

                new BinaryPrefixComparator(Bytes.toBytes("na"))   //表中存在以na打头的列name,过滤结果为所有行的该列数据

                      );

             

        //基于列名(即Qualifier)前缀过滤数据的ColumnPrefixFilter

        filter = new ColumnPrefixFilter("na".getBytes());

       

        //基于列名(即Qualifier)多个前缀过滤数据的MultipleColumnPrefixFilter

        byte[][] prefixes = new byte[][] {Bytes.toBytes("na"), Bytes.toBytes("me")};

        filter = new MultipleColumnPrefixFilter(prefixes);

 

        //为查询设置过滤条件

        scan.setFilter(filter);

       

       

       

              scan.addFamily(Bytes.toBytes("base_info"));

        //一行

//            Result result = table.get(get);

        //多行的数据

              ResultScanner scanner = table.getScanner(scan);

              for(Result r : scanner){

                     /**

                     for(KeyValue kv : r.list()){

                            String family = new String(kv.getFamily());

                            System.out.println(family);

                            String qualifier = new String(kv.getQualifier());

                            System.out.println(qualifier);

                            System.out.println(new String(kv.getValue()));

                     }

                     */

            //直接从result中取到某个特定的value

                     byte[] value = r.getValue(Bytes.toBytes("base_info"), Bytes.toBytes("name"));

                     System.out.println(new String(value));

              }

              table.close();

       }

 

 

 

Hbase Filter过滤器查询详解

标签:lte   list   line   2.4   span   new   red   color   width   

原文地址:https://www.cnblogs.com/Transkai/p/10727257.html

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