HBase Filter 过滤器之RowFilter详解

前言：本文详细介绍了HBase RowFilter过滤器Java&Shell API的使用，并贴出了相关示例代码以供参考。RowFilter 基于行键进行过滤，在工作中涉及到需要通过HBase Rowkey进行数据过滤时可以考虑使用它。比较器细节及原理请参照之前的更文：HBase Filter 过滤器之比较器 Comparator 原理及源码学习

一。Java Api
头部代码

public class RowFilterDemo {

private static boolean isok = false;
private static String tableName = "test";
private static String[] cfs = new String[]{"f"};
private static String[] data = new String[]{"row-ac:f:c1:v1", "row-ab:f:c2:v2", "row-bc:f:c3:v3", "row-abc:f:c4:v4"};

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

    MyBase myBase = new MyBase();
    Connection connection = myBase.createConnection();
    if (isok) {
        myBase.deleteTable(connection, tableName);
        myBase.createTable(connection, tableName, cfs);
        myBase.putRows(connection, tableName, data); // 造数据
    }
    Table table = connection.getTable(TableName.valueOf(tableName));
    Scan scan = new Scan();

中部代码 向右滑动滚动条可查看输出结果。

1. BinaryComparator 构造过滤器
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-ac]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.NOT_EQUAL, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-ab, row-abc, row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.GREATER, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.GREATER_OR_EQUAL, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-ac, row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.LESS, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-ab, row-abc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.LESS_OR_EQUAL, new BinaryComparator(Bytes.toBytes("row-ac"))); // [row-ab, row-abc, row-ac]
2. BinaryPrefixComparator 构造过滤器
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // [row-ab, row-abc, row-ac]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.NOT_EQUAL, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // [row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.GREATER, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // [row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.GREATER_OR_EQUAL, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // [row-ab, row-abc, row-ac, row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.LESS, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // []
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.LESS_OR_EQUAL, new BinaryPrefixComparator(Bytes.toBytes("row-a"))); // [row-ab, row-abc, row-ac]
3. SubstringComparator 构造过滤器
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new SubstringComparator("ab")); // [row-ab, row-abc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.NOT_EQUAL, new SubstringComparator("ab")); // [row-ac, row-bc]
4. RegexStringComparator 构造过滤器
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.NOT_EQUAL, new RegexStringComparator("abc")); // [row-ab, row-ac, row-bc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new RegexStringComparator("abc")); // [row-abc]
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new RegexStringComparator("a")); // [row-ab, row-abc, row-ac]
5. NullComparator 构造过滤器
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.EQUAL, new NullComparator()); // []
   RowFilter rowFilter = new RowFilter(CompareFilter.CompareOp.NOT_EQUAL, new NullComparator()); // [row-ab, row-abc, row-ac, row-bc]

尾部代码

    scan.setFilter(rowFilter);
    ResultScanner scanner = table.getScanner(scan);
    Iterator<Result> iterator = scanner.iterator();
    LinkedList<String> rowkeys = new LinkedList<>();
    while (iterator.hasNext()) {
        Result result = iterator.next();
        String rowkey = Bytes.toString(result.getRow());
        rowkeys.add(rowkey);
    }
    System.out.println(rowkeys);
    scanner.close();
    table.close();
    connection.close();
}

}
二。Shell Api

1. BinaryComparator 构造过滤器

方式一：

hbase(main):006:0> scan 'test',{FILTER=>"RowFilter(=,'binary:row-ab')"}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
1 row(s) in 0.0140 seconds
支持的比较运算符：= != > >= < <=，不再一一举例。

方式二：

import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.BinaryComparator
import org.apache.hadoop.hbase.filter.RowFilter

hbase(main):016:0> scan 'test',{FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), BinaryComparator.new(Bytes.toBytes('row-ab')))}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
1 row(s) in 0.0310 seconds
支持的比较运算符：LESS、LESS_OR_EQUAL、EQUAL、NOT_EQUAL、GREATER、GREATER_OR_EQUAL，不再一一举例。

推荐使用方式一，更简洁方便。

1. BinaryPrefixComparator 构造过滤器

方式一：

hbase(main):023:0> scan 'test',{FILTER=>"RowFilter(=,'binaryprefix:row-ab')"}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
row-abc column=f:c4, timestamp=1588156704669, value=v4
2 row(s) in 0.0360 seconds
方式二：

import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.BinaryPrefixComparator
import org.apache.hadoop.hbase.filter.RowFilter

hbase(main):027:0> scan 'test',{FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), BinaryPrefixComparator.new(Bytes.toBytes('row-ab')))}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
row-abc column=f:c4, timestamp=1588156704669, value=v4
2 row(s) in 0.0110 seconds
其它同上。

1. SubstringComparator 构造过滤器

方式一：

hbase(main):001:0> scan 'test',{FILTER=>"RowFilter(=,'substring:row-ab')"}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
row-abc column=f:c4, timestamp=1588156704669, value=v4
2 row(s) in 0.3200 seconds
方式二：

import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.SubstringComparator
import org.apache.hadoop.hbase.filter.RowFilter

hbase(main):007:0> scan 'test',{FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), SubstringComparator.new('row-ab'))}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
row-abc column=f:c4, timestamp=1588156704669, value=v4
2 row(s) in 0.0230 seconds
区别于上的是这里直接传入字符串进行比较，且只支持EQUAL和NOT_EQUAL两种比较符。

1. RegexStringComparator 构造过滤器

import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.RegexStringComparator
import org.apache.hadoop.hbase.filter.RowFilter

hbase(main):007:0> scan 'test',{FILTER => RowFilter.new(CompareFilter::CompareOp.valueOf('EQUAL'), RegexStringComparator.new('row-ab'))}
ROW COLUMN+CELL
row-ab column=f:c2, timestamp=1588156704669, value=v2
row-abc column=f:c4, timestamp=1588156704669, value=v4
2 row(s) in 0.0230 seconds
该比较器直接传入字符串进行比较，且只支持EQUAL和NOT_EQUAL两种比较符。若想使用第一种卖手游账号方式可以传入regexstring试一下，我的版本有点低暂时不支持，不再演示了。

注意这里的正则匹配指包含关系，对应底层find()方法。

此外，RowFilter 不支持使用LongComparator比较器，且BitComparator、NullComparator 比较器用之甚少，也不再介绍。