RowFilter用于过滤row key Operator Description LESS 小于 LESS_OR_EQUAL 小于等于 EQUAL 等于 NOT_EQUAL 不等于 GREATER_OR_EQUAL 大于等于 GREATER 大于 NO_OP 排除所有 Comparator Description BinaryComparator 使用Bytes.compareTo()比较 BinaryPrefix
RowFilter用于过滤row key
| Operator | Description |
|---|---|
LESS |
小于 |
LESS_OR_EQUAL |
小于等于 |
EQUAL |
等于 |
NOT_EQUAL |
不等于 |
GREATER_OR_EQUAL |
大于等于 |
GREATER |
大于 |
NO_OP |
排除所有 |
| Comparator | Description |
|---|---|
BinaryComparator |
使用Bytes.compareTo()比较 |
BinaryPrefixComparator |
和BinaryComparator差不多，从前面开始比较 |
NullComparator |
Does?not compare against an actual value but whether a given one is?null, or not?null. |
BitComparator |
Performs?a bitwise comparison, providing a?BitwiseOp?class with?AND,?OR, and?XOR?operators. |
RegexStringComparator |
正则表达式 |
SubstringComparator |
把数据当成字符串，用contains()来判断 |
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.HColumnDescriptor;
import org.apache.hadoop.hbase.HTableDescriptor;
import org.apache.hadoop.hbase.client.HBaseAdmin;
import org.apache.hadoop.hbase.client.HTable;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.ResultScanner;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.filter.BinaryComparator;
import org.apache.hadoop.hbase.filter.BinaryPrefixComparator;
import org.apache.hadoop.hbase.filter.CompareFilter;
import org.apache.hadoop.hbase.filter.Filter;
import org.apache.hadoop.hbase.filter.RegexStringComparator;
import org.apache.hadoop.hbase.filter.RowFilter;
import org.apache.hadoop.hbase.filter.SubstringComparator;
public class TestHbaseRowFilter {
String tableName = "test_row_filter";
Configuration config = HBaseConfiguration.create();
/**
* 部分代码来自hbase权威指南
* @throws IOException
*/
public void testRowFilter() throws IOException {
HTable table = new HTable(config, tableName);
Scan scan = new Scan();
System.out.println("小于等于row010的行");
Filter filter1 = new RowFilter(CompareFilter.CompareOp.LESS_OR_EQUAL,
new BinaryComparator("row010".getBytes()));
scan.setFilter(filter1);
ResultScanner scanner1 = table.getScanner(scan);
for (Result res : scanner1) {
System.out.println(res);
}
scanner1.close();
System.out.println("正则获取结尾为5的行");
Filter filter2 = new RowFilter(CompareFilter.CompareOp.EQUAL,
new RegexStringComparator(".*5$"));
scan.setFilter(filter2);
ResultScanner scanner2 = table.getScanner(scan);
for (Result res : scanner2) {
System.out.println(res);
}
scanner2.close();
System.out.println("包行有5的行");
Filter filter3 = new RowFilter(CompareFilter.CompareOp.EQUAL,
new SubstringComparator("5"));
scan.setFilter(filter3);
ResultScanner scanner3 = table.getScanner(scan);
for (Result res : scanner3) {
System.out.println(res);
}
scanner3.close();
System.out.println("开头是row01的");
Filter filter4 = new RowFilter(CompareFilter.CompareOp.EQUAL,
new BinaryPrefixComparator("row01".getBytes()));
scan.setFilter(filter4);
ResultScanner scanner4 = table.getScanner(scan);
for (Result res : scanner4) {
System.out.println(res);
}
scanner3.close();
}
/**
* 初始化数据
*/
public void init() {
// 创建表和初始化数据
try {
HBaseAdmin admin = new HBaseAdmin(config);
if (!admin.tableExists(tableName)) {
HTableDescriptor htd = new HTableDescriptor(tableName);
HColumnDescriptor hcd1 = new HColumnDescriptor("data");
htd.addFamily(hcd1);
HColumnDescriptor hcd2 = new HColumnDescriptor("url");
htd.addFamily(hcd2);
admin.createTable(htd);
}
HTable table = new HTable(config, tableName);
table.setAutoFlush(false);
int count = 50;
for (int i = 1; i
<h2 id="输出结果">输出结果</h2>
<pre class="brush:php;toolbar:false">小于等于row010的行
keyvalues={row001/data:col1/1364133382268/Put/vlen=7, row001/url:col1/1364133382268/Put/vlen=6}
keyvalues={row002/data:col2/1364133382268/Put/vlen=7, row002/url:col2/1364133382268/Put/vlen=6}
keyvalues={row003/data:col3/1364133382268/Put/vlen=7, row003/url:col3/1364133382268/Put/vlen=6}
keyvalues={row004/data:col4/1364133382268/Put/vlen=7, row004/url:col4/1364133382268/Put/vlen=6}
keyvalues={row005/data:col5/1364133382268/Put/vlen=7, row005/url:col5/1364133382268/Put/vlen=6}
keyvalues={row006/data:col6/1364133382268/Put/vlen=7, row006/url:col6/1364133382268/Put/vlen=6}
keyvalues={row007/data:col7/1364133382268/Put/vlen=7, row007/url:col7/1364133382268/Put/vlen=6}
keyvalues={row008/data:col8/1364133382268/Put/vlen=7, row008/url:col8/1364133382268/Put/vlen=6}
keyvalues={row009/data:col9/1364133382268/Put/vlen=7, row009/url:col9/1364133382268/Put/vlen=6}
keyvalues={row010/data:col0/1364133382268/Put/vlen=7, row010/url:col0/1364133382268/Put/vlen=6}
正则获取结尾为5的行
keyvalues={row005/data:col5/1364133382268/Put/vlen=7, row005/url:col5/1364133382268/Put/vlen=6}
keyvalues={row015/data:col5/1364133382268/Put/vlen=7, row015/url:col5/1364133382268/Put/vlen=6}
keyvalues={row025/data:col5/1364133382268/Put/vlen=7, row025/url:col5/1364133382268/Put/vlen=6}
keyvalues={row035/data:col5/1364133382268/Put/vlen=7, row035/url:col5/1364133382268/Put/vlen=6}
keyvalues={row045/data:col5/1364133382268/Put/vlen=7, row045/url:col5/1364133382268/Put/vlen=6}
包行有5的行
keyvalues={row005/data:col5/1364133382268/Put/vlen=7, row005/url:col5/1364133382268/Put/vlen=6}
keyvalues={row015/data:col5/1364133382268/Put/vlen=7, row015/url:col5/1364133382268/Put/vlen=6}
keyvalues={row025/data:col5/1364133382268/Put/vlen=7, row025/url:col5/1364133382268/Put/vlen=6}
keyvalues={row035/data:col5/1364133382268/Put/vlen=7, row035/url:col5/1364133382268/Put/vlen=6}
keyvalues={row045/data:col5/1364133382268/Put/vlen=7, row045/url:col5/1364133382268/Put/vlen=6}
keyvalues={row050/data:col0/1364133382268/Put/vlen=7, row050/url:col0/1364133382268/Put/vlen=6}
开头是row01的
keyvalues={row010/data:col0/1364133382268/Put/vlen=7, row010/url:col0/1364133382268/Put/vlen=6}
keyvalues={row011/data:col1/1364133382268/Put/vlen=7, row011/url:col1/1364133382268/Put/vlen=6}
keyvalues={row012/data:col2/1364133382268/Put/vlen=7, row012/url:col2/1364133382268/Put/vlen=6}
keyvalues={row013/data:col3/1364133382268/Put/vlen=7, row013/url:col3/1364133382268/Put/vlen=6}
keyvalues={row014/data:col4/1364133382268/Put/vlen=7, row014/url:col4/1364133382268/Put/vlen=6}
keyvalues={row015/data:col5/1364133382268/Put/vlen=7, row015/url:col5/1364133382268/Put/vlen=6}
keyvalues={row016/data:col6/1364133382268/Put/vlen=7, row016/url:col6/1364133382268/Put/vlen=6}
keyvalues={row017/data:col7/1364133382268/Put/vlen=7, row017/url:col7/1364133382268/Put/vlen=6}
keyvalues={row018/data:col8/1364133382268/Put/vlen=7, row018/url:col8/1364133382268/Put/vlen=6}
keyvalues={row019/data:col9/1364133382268/Put/vlen=7, row019/url:col9/1364133382268/Put/vlen=6}
参考
hbase权威指南
原文地址：hbase RowFilter, 感谢原作者分享。
What are stored procedures in MySQL?May 01, 2025 am 12:27 AMStored procedures are precompiled SQL statements in MySQL for improving performance and simplifying complex operations. 1. Improve performance: After the first compilation, subsequent calls do not need to be recompiled. 2. Improve security: Restrict data table access through permission control. 3. Simplify complex operations: combine multiple SQL statements to simplify application layer logic.
How does query caching work in MySQL?May 01, 2025 am 12:26 AMThe working principle of MySQL query cache is to store the results of SELECT query, and when the same query is executed again, the cached results are directly returned. 1) Query cache improves database reading performance and finds cached results through hash values. 2) Simple configuration, set query_cache_type and query_cache_size in MySQL configuration file. 3) Use the SQL_NO_CACHE keyword to disable the cache of specific queries. 4) In high-frequency update environments, query cache may cause performance bottlenecks and needs to be optimized for use through monitoring and adjustment of parameters.
What are the advantages of using MySQL over other relational databases?May 01, 2025 am 12:18 AMThe reasons why MySQL is widely used in various projects include: 1. High performance and scalability, supporting multiple storage engines; 2. Easy to use and maintain, simple configuration and rich tools; 3. Rich ecosystem, attracting a large number of community and third-party tool support; 4. Cross-platform support, suitable for multiple operating systems.
How do you handle database upgrades in MySQL?Apr 30, 2025 am 12:28 AMThe steps for upgrading MySQL database include: 1. Backup the database, 2. Stop the current MySQL service, 3. Install the new version of MySQL, 4. Start the new version of MySQL service, 5. Recover the database. Compatibility issues are required during the upgrade process, and advanced tools such as PerconaToolkit can be used for testing and optimization.
What are the different backup strategies you can use for MySQL?Apr 30, 2025 am 12:28 AMMySQL backup policies include logical backup, physical backup, incremental backup, replication-based backup, and cloud backup. 1. Logical backup uses mysqldump to export database structure and data, which is suitable for small databases and version migrations. 2. Physical backups are fast and comprehensive by copying data files, but require database consistency. 3. Incremental backup uses binary logging to record changes, which is suitable for large databases. 4. Replication-based backup reduces the impact on the production system by backing up from the server. 5. Cloud backups such as AmazonRDS provide automation solutions, but costs and control need to be considered. When selecting a policy, database size, downtime tolerance, recovery time, and recovery point goals should be considered.
What is MySQL clustering?Apr 30, 2025 am 12:28 AMMySQLclusteringenhancesdatabaserobustnessandscalabilitybydistributingdataacrossmultiplenodes.ItusestheNDBenginefordatareplicationandfaulttolerance,ensuringhighavailability.Setupinvolvesconfiguringmanagement,data,andSQLnodes,withcarefulmonitoringandpe
How do you optimize database schema design for performance in MySQL?Apr 30, 2025 am 12:27 AMOptimizing database schema design in MySQL can improve performance through the following steps: 1. Index optimization: Create indexes on common query columns, balancing the overhead of query and inserting updates. 2. Table structure optimization: Reduce data redundancy through normalization or anti-normalization and improve access efficiency. 3. Data type selection: Use appropriate data types, such as INT instead of VARCHAR, to reduce storage space. 4. Partitioning and sub-table: For large data volumes, use partitioning and sub-table to disperse data to improve query and maintenance efficiency.
How can you optimize MySQL performance?Apr 30, 2025 am 12:26 AMTooptimizeMySQLperformance,followthesesteps:1)Implementproperindexingtospeedupqueries,2)UseEXPLAINtoanalyzeandoptimizequeryperformance,3)Adjustserverconfigurationsettingslikeinnodb_buffer_pool_sizeandmax_connections,4)Usepartitioningforlargetablestoi
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.
VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft
EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function
SublimeText3 Mac version
God-level code editing software (SublimeText3)
