Hbase Filter过滤器查询详解

Posted 2021-02-16 transkai

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(" ")).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();        }