hbase的过滤器查询

  hbase的过滤器有很多：大致分为两大类：比较过滤器和专用过滤器，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 EQUALSubstringComparator 判断提供的子串是否出现在 value 中。

1. 比较过滤器

//行键过滤器 RowFilterFilter filter1 = new RowFilter(CompareOp.LESS_OR_EQUAL, newBinaryComparator(Bytes.toBytes("user0000")));scan.setFilter(filter1);

//列簇过滤器 FamilyFilterFilter filter1 = new FamilyFilter(CompareOp.LESS, newBinaryComparator(Bytes.toBytes("base_info")));scan.setFilter(filter1);

//列过滤器 QualifierFilterFilter filter = new QualifierFilter(CompareOp.LESS_OR_EQUAL, newBinaryComparator(Bytes.toBytes("name")));scan.setFilter(filter1);

//值过滤器 ValueFilterFilter filter = new ValueFilter(CompareOp.EQUAL, new SubstringComparator("zhangsan") );scan.setFilter(filter1); 

//时间戳过滤器 TimestampsFilterList tss = new ArrayList();tss.add(1495398833002l);Filter filter1 = new TimestampsFilter(tss);scan.setFilter(filter1);

2.专用过滤器

//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); 

//单列值排除器 SingleColumnValueExcludeFilter -----返回排除了该列的结果SingleColumnValueExcludeFilter filter = new SingleColumnValueExcludeFilter( 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);

//前缀过滤器 PrefixFilter----针对行键Filter filter = new PrefixFilter(Bytes.toBytes("row1"));scan.setFilter(filter1); 

//列前缀过滤器 ColumnPrefixFilterFilter filter = new ColumnPrefixFilter(Bytes.toBytes("qual2"));scan.setFilter(filter1); 

实战案例：

public class HBase_Filter01 {    private static String ZK_KEY = "hbase.zookeeper.quorum";    private static String ZK_VALUE = "hadoop01:2181,hadoop02:2181,hadoop03:2181";    private static Configuration conf;    private static Connection connection;    private static Admin admin;    static {        conf = HBaseConfiguration.create();        conf.set(ZK_KEY,ZK_VALUE);        try {            connection= ConnectionFactory.createConnection(conf);            admin=connection.getAdmin();        } catch (IOException e) {            e.printStackTrace();        }    }    public static void main(String[] args) {        Scan scan=new Scan();        ValueFilter filter = new ValueFilter(CompareFilter.CompareOp.EQUAL, new SubstringComparator("a"));        scan.setFilter(filter);        TableName tableName =TableName.valueOf("user_info");        try {            Table table = connection.getTable(tableName);            ResultScanner scanner = table.getScanner(scan);            Iterator iterator=scanner.iterator();            while(iterator.hasNext()){                 Result result = iterator.next();                System.out.println(result.list());                 byte[] row = result.getRow();                System.out.println(new String(row));            }        } catch (IOException e) {            e.printStackTrace();        }    }}