大家好,我是考100分的小小码 ,祝大家学习进步,加薪顺利呀。今天说一说HBase Filter 过滤器之RowFilter详解「建议收藏」,希望您对编程的造诣更进一步.
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();
代码100分
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
代码100分 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
代码100分 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。
2. 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。
3. 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。
4. 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。
查看文章全部源代码请访以下GitHub地址:
https://github.com/zhoupengbo/demos-bigdata/blob/master/hbase/hbase-filters-demos/src/main/java/com/zpb/demos/RowFilterDemo.java
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