hbase的过滤器有不少:大体分为两大类:比较过滤器和专用过滤器,过滤器的做用是在服务端判断数据是否知足条件,而后只将知足条件的数据返回给客户端;
hbase 过滤器的比较运算符:数组
LESS ----- < LESS_OR_EQUAL ----- <= EQUAL ----- = NOT_EQUAL ----- <> GREATER_OR_EQUAL ----- >= GREATER ----- > NO_OP #排除全部
HBase 过滤器的比较器(指定比较机制):ide
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如今 value 中。
//行键过滤器 RowFilter Filter filter1 = new RowFilter(CompareOp.LESS_OR_EQUAL, new BinaryComparator(Bytes.toBytes("user0000"))); scan.setFilter(filter1);
//列簇过滤器 FamilyFilter Filter filter1 = new FamilyFilter(CompareOp.LESS, new BinaryComparator(Bytes.toBytes("base_info"))); scan.setFilter(filter1);
//列过滤器 QualifierFilter Filter filter = new QualifierFilter(CompareOp.LESS_OR_EQUAL, new BinaryComparator(Bytes.toBytes("name"))); scan.setFilter(filter1);
//值过滤器 ValueFilter Filter filter = new ValueFilter(CompareOp.EQUAL, new SubstringComparator("zhangsan") ); scan.setFilter(filter1);
//时间戳过滤器 TimestampsFilter List<Long> tss = new ArrayList<Long>(); tss.add(1495398833002l); Filter filter1 = new TimestampsFilter(tss); scan.setFilter(filter1);
//单列值过滤器 SingleColumnValueFilter ----会返回知足条件的整行 SingleColumnValueFilter filter = new SingleColumnValueFilter( Bytes.toBytes("colfam1"), Bytes.toBytes("col-5"), CompareFilter.CompareOp.NOT_EQUAL, new SubstringComparator("val-5")); filter.setFilterIfMissing(true); //若是不设置为 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); //若是不设置为 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 ColumnPrefixFilter Filter filter = new ColumnPrefixFilter(Bytes.toBytes("qual2")); scan.setFilter(filter1);
实战案例:oop
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<Result> 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(); } } }