本文主要是hbase的表操作、数据操作、数据查询过滤等，如果对JDBC或ADO有了解，容易理解HBASE API。
hbase版本是2.0。
1、为了方便先贴helper的部分代码（文末git上有完整的测试代码），主要是为了复用Connection。
public class HBaseHelper implements Closeable {
private Configuration configuration = null;
private Connection connection = null;
private Admin admin = null;
private HBaseHelper(Configuration configuration) throws IOException {
this.configuration = configuration;
this.connection = ConnectionFactory.createConnection(this.configuration);
admin = this.connection.getAdmin();
}
public static HBaseHelper getHBaseHelper(Configuration configuration) throws IOException {
return new HBaseHelper(configuration);
}
@Override
public void close() throws IOException {
admin.close();
connection.close();
}
public Connection getConnection() {
return connection;
}
public Configuration getConfiguration() {
return configuration;
}
... ...
｝
初始化，用来初始化hbase配置，连接hbase，获取本文中的hbase辅助操作类HbaseHelper。
//初始化
private void setUp() throws IOException{
conf = HBaseConfiguration.create();
conf.set("hbase.master","192.168.31.10");
//The port the HBase Master should bind to.
// conf.set("hbase.master.port","16000");
//The port for the HBase Master web UI. Set to -1 if you do not want a UI instance run.
// conf.set("hbase.master.info.port","16010");
//The port the HBase RegionServer binds to.
// conf.set("hbase.regionserver.port","16020");
//The port for the HBase RegionServer web UI Set to -1 if you do not want the RegionServer UI to run.
// conf.set("hbase.regionserver.info.port","16030");
conf.set("hbase.zookeeper.quorum","192.168.31.10");
//Property from ZooKeeper’s config zoo.cfg. The port at which the clients will connect.
// HBase数据库使用的端口
//conf.set("hbase.zookeeper.property.clientPort", "2181");
//单机
conf.set("hbase.rootdir","file:///opt/hbase_data");
conf.set("hbase.zookeeper.property.dataDir","/opt/hbase_data/zookeeper");
helper = HBaseHelper.getHBaseHelper(conf);
}
2、命名空间、表创建、删除、exist等
public void createNamespace(String namespace) {
try {
NamespaceDescriptor nd = NamespaceDescriptor.create(namespace).build();
admin.createNamespace(nd);
} catch (Exception e) {
System.err.println("Error: " + e.getMessage());
}
}
public void dropNamespace(String namespace, boolean force) {
try {
if (force) {
TableName[] tableNames = admin.listTableNamesByNamespace(namespace);
for (TableName name : tableNames) {
admin.disableTable(name);
admin.deleteTable(name);
}
}
} catch (Exception e) {
// ignore
}
try {
admin.deleteNamespace(namespace);
} catch (IOException e) {
System.err.println("Error: " + e.getMessage());
}
}
public boolean existsTable(String table)
throws IOException {
return existsTable(TableName.valueOf(table));
}
public boolean existsTable(TableName table)
throws IOException {
return admin.tableExists(table);
}
public void createTable(String table, String... colfams)
throws IOException {
createTable(TableName.valueOf(table), 1, null, colfams);
}
public void createTable(TableName table, String... colfams)
throws IOException {
createTable(table, 1, null, colfams);
}
public void createTable(String table, int maxVersions, String... colfams)
throws IOException {
createTable(TableName.valueOf(table), maxVersions, null, colfams);
}
public void createTable(TableName table, int maxVersions, String... colfams)
throws IOException {
createTable(table, maxVersions, null, colfams);
}
public void createTable(String table, byte[][] splitKeys, String... colfams)
throws IOException {
createTable(TableName.valueOf(table), 1, splitKeys, colfams);
}
public void createTable(TableName table, int maxVersions, byte[][] splitKeys,
String... colfams)
throws IOException {
//表描述器构造器
TableDescriptorBuilder tableDescriptorBuilder = TableDescriptorBuilder.newBuilder(table);
//列族描述构造器
ColumnFamilyDescriptorBuilder cfDescBuilder;
//列族描述器
ColumnFamilyDescriptor cfDesc;
for (String cf : colfams) {
cfDescBuilder = ColumnFamilyDescriptorBuilder.newBuilder(Bytes.toBytes(cf));
cfDescBuilder.setMaxVersions(maxVersions);
cfDesc = cfDescBuilder.build();
tableDescriptorBuilder.setColumnFamily(cfDesc);
}
//获得表描述器
TableDescriptor tableDescriptor = tableDescriptorBuilder.build();
if (splitKeys != null) {
admin.createTable(tableDescriptor, splitKeys);
} else {
admin.createTable(tableDescriptor);
}
}
//禁用表
public void disableTable(String table) throws IOException {
disableTable(TableName.valueOf(table));
}
public void disableTable(TableName table) throws IOException {
admin.disableTable(table);
}
public void dropTable(String table) throws IOException {
dropTable(TableName.valueOf(table));
}
//删除前，先禁用表
public void dropTable(TableName table) throws IOException {
if (existsTable(table)) {
if (admin.isTableEnabled(table)) disableTable(table);
admin.deleteTable(table);
}
}
样例：
//插入testtable表数据
private void initTestTable() throws IOException{
String tableNameString = "testtable";
if(helper.existsTable(tableNameString)){
helper.disableTable(tableNameString);
helper.dropTable(tableNameString);
}
helper.createTable(tableNameString,"info","ex","memo");
helper.put(tableNameString,"row1","info","username","admin");
helper.put(tableNameString,"row1","ex","addr","北京大道");
helper.put(tableNameString,"row1","memo","detail","超级用户，地址：北京大道");
helper.put(tableNameString,"row2","info","username","guest");
helper.put(tableNameString,"row2","ex","addr","全国各地");
helper.put(tableNameString,"row2","memo","detail","游客，地址：全国到处都是");
helper.close();
}
2、插入（或是更新）数据
public void put(String table, String row, String fam, String qual,
String val) throws IOException {
put(TableName.valueOf(table), row, fam, qual, val);
}
//插入或更新单行
public void put(TableName table, String row, String fam, String qual,
String val) throws IOException {
Table tbl = connection.getTable(table);
Put put = new Put(Bytes.toBytes(row));
put.addColumn(Bytes.toBytes(fam), Bytes.toBytes(qual), Bytes.toBytes(val));
tbl.put(put);
tbl.close();
}
public void put(String table, String row, String fam, String qual, long ts,
String val) throws IOException {
put(TableName.valueOf(table), row, fam, qual, ts, val);
}
//带时间戳插入或更新单行
public void put(TableName table, String row, String fam, String qual, long ts,
String val) throws IOException {
Table tbl = connection.getTable(table);
Put put = new Put(Bytes.toBytes(row));
put.addColumn(Bytes.toBytes(fam), Bytes.toBytes(qual), ts,
Bytes.toBytes(val));
tbl.put(put);
tbl.close();
}
//插入或者更新一个rowKey数据，一个Put里有一个rowKey，可能有多个列族和列名
public void put(String tableNameString, Put put) throws IOException {
TableName tableName = TableName.valueOf(tableNameString);
Table table = connection.getTable(tableName);
if (put != null && put.size() > 0) {
table.put(put);
}
table.close();
}
2.1、批量插入，根据实际的业务来组装数据，最终就是利用API放入put列表
//批量插入数据,list里每个map就是一条数据，并且按照rowKey columnFamily columnName columnValue放入map的key和value
public void bulkInsert(String tableNameString, List<Map<String, Object>> list) throws IOException {
Table table = connection.getTable(TableName.valueOf(tableNameString));
List<Put> puts = new ArrayList<Put>();
if (list != null && list.size() > 0) {
for (Map<String, Object> map : list) {
Put put = new Put(Bytes.toBytes(map.get("rowKey").toString()));
put.addColumn(Bytes.toBytes(map.get("columnFamily").toString()),
Bytes.toBytes(map.get("columnName").toString()),
Bytes.toBytes(map.get("columnValue").toString()));
puts.add(put);
}
}
table.put(puts);
table.close();
}
//批量插入，外部组装put放入list
public void bulkInsert2(String tableNameString, List<Put> puts) throws IOException {
Table table = connection.getTable(TableName.valueOf(tableNameString));
if (puts != null && puts.size() > 0) {
table.put(puts);
}
table.close();
}
样例：
//批量插入
private void bulkInsertTestTable() throws IOException{
String tableNameString = "testtable";
if(!helper.existsTable(tableNameString)){
helper.createTable(tableNameString,"info","ex","memo");
}
System.out.println(".........批量插入数据start.........");
List<Map<String,Object>> mapList = new ArrayList<>();
for(int i=1;i<201;i++){
Map<String,Object> map = new HashMap<>();
map.put("rowKey","testKey"+i);
map.put("columnFamily","info");
map.put("columnName","username");
map.put("columnValue","guest"+i);
map.put("rowKey","testKey"+i);
map.put("columnFamily","ex");
map.put("columnName","addr");
map.put("columnValue","北京路"+i+"号");
map.put("rowKey","testKey"+i);
map.put("columnFamily","memo");
map.put("columnName","detail");
map.put("columnValue","联合国地球村北京路第"+i+"号");
mapList.add(map);
}
helper.bulkInsert(tableNameString,mapList);
System.out.println(".........批量插入数据end.........");
}
//批量插入2
private void insertByRowKey(String table,String rowKey) throws IOException{
Put put = new Put(Bytes.toBytes(rowKey));
String columnFamily ;
String columnName ;
String columnValue ;
for(int i=0;i<10;i++){
columnFamily = "info";
columnName = "username"+i;
columnValue = "user111";
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
columnFamily = "ex";
columnName = "addr"+i;
columnValue = "street 111";
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
columnFamily = "memo";
columnName = "detail"+i;
columnValue = "sssss zzz 111222 ";
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
}
System.out.println("----> put size:"+put.size());
helper.put(table,put);
}
private void bulkInsertTestTable2(String tableNameString) throws IOException{
// String tableNameString = "testtable";
if(!helper.existsTable(tableNameString)){
helper.createTable(tableNameString,"info","ex","memo");
}
List<Put> puts = new ArrayList<>();
for(int i=0;i<10;i++){
String rowKey = "rowKey"+i;
Put put = new Put(Bytes.toBytes(rowKey));
String columnFamily = "info";
String columnName = "username2";
String columnValue = "user"+i;
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
columnFamily = "ex";
columnName = "addr2";
columnValue = "street "+i;
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
columnFamily = "memo";
columnName = "detail2";
columnValue = "aazzdd "+i;
put.addColumn(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName),Bytes.toBytes(columnValue));
System.out.println("put size:"+put.size());
puts.add(put);
}
helper.bulkInsert2(tableNameString,puts);
}
3、删除数据，由于hbase数据是三个维度的，所以删除数据有多种操作
//根据rowKey删除所有行数据
public void deleteByKey(String tableNameString,String rowKey) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Delete delete = new Delete(Bytes.toBytes(rowKey));
table.delete(delete);
table.close();
}
//根据rowKey和列族删除所有行数据
public void deleteByKeyAndFamily(String tableNameString,String rowKey,String columnFamily) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Delete delete = new Delete(Bytes.toBytes(rowKey));
delete.addFamily(Bytes.toBytes(columnFamily));
table.delete(delete);
table.close();
}
//根据rowKey、列族删除多个列的数据
public void deleteByKeyAndFC(String tableNameString,String rowKey,
String columnFamily,List<String> columnNames) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Delete delete = new Delete(Bytes.toBytes(rowKey));
for(String columnName:columnNames){
delete.addColumns(Bytes.toBytes(columnFamily),Bytes.toBytes(columnName));
}
table.delete(delete);
table.close();
}
4、基本的查询，唯一要注意的是cell里的value必须按位移和长度来取
//根据rowkey，获取所有列族和列数据
public List<Cell> getRowByKey(String tableNameString,String rowKey) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Get get = new Get(Bytes.toBytes(rowKey));
Result result = table.get(get);
// Cell[] cells = result.rawCells();
List<Cell> list = result.listCells();
table.close();
return list;
}
//从Cell取Array要加上位移和长度，不然数据不正确
public void dumpResult(Result result) {
for (Cell cell : result.rawCells()) {
System.out.println("Cell: " + cell +
", Value: " + Bytes.toString(cell.getValueArray(),
cell.getValueOffset(), cell.getValueLength()));
}
}
5、过滤，这个是HBASE查询的重要部分
5.1、根据rowKey来过滤
//根据rowKey过滤数据，rowKey可以使用正则表达式
//返回rowKey和Cells的键值对
public Map<String,List<Cell>> filterByRowKeyRegex(String tableNameString,String rowKey,CompareOperator operator) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Scan scan = new Scan();
//使用正则
RowFilter filter = new RowFilter(operator,new RegexStringComparator(rowKey));
//包含子串匹配,不区分大小写。
// RowFilter filter = new RowFilter(operator,new SubstringComparator(rowKey));
scan.setFilter(filter);
ResultScanner scanner = table.getScanner(scan);
Map<String,List<Cell>> map = new HashMap<>();
for(Result result:scanner){
map.put(Bytes.toString(result.getRow()),result.listCells());
}
table.close();
return map;
}
5.2、根据列值、列值正则等方式过滤
//根据列族，列名，列值（支持正则）查找数据
//返回值：如果查询到值，会返回所有匹配的rowKey下的各列族、列名的所有数据（即使查询的时候这些列族和列名并不匹配）
public Map<String,List<Cell>> filterByValueRegex(String tableNameString,String family,String colName,
String value,CompareOperator operator) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
Scan scan = new Scan();
//正则匹配
SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes(family),
Bytes.toBytes(colName),operator,new RegexStringComparator(value));
//完全匹配
// SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes(family),
// Bytes.toBytes(colName),operator,Bytes.toBytes(value));
//SingleColumnValueExcludeFilter排除列值
//要过滤的列必须存在，如果不存在，那么这些列不存在的数据也会返回。如果不想让这些数据返回,设置setFilterIfMissing为true
filter.setFilterIfMissing(true);
scan.setFilter(filter);
ResultScanner scanner = table.getScanner(scan);
Map<String,List<Cell>> map = new HashMap<>();
for(Result result:scanner){
map.put(Bytes.toString(result.getRow()),result.listCells());
}
return map;
}
5.3、根据列名前缀、列名正则、多个列名等过滤
//根据列名前缀过滤数据
public Map<String,List<Cell>> filterByColumnPrefix(String tableNameString,String prefix) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
//列名前缀匹配
ColumnPrefixFilter filter = new ColumnPrefixFilter(Bytes.toBytes(prefix));
//QualifierFilter 用于列名多样性匹配过滤
// QualifierFilter filter = new QualifierFilter(CompareOperator.EQUAL,new SubstringComparator(prefix));
//多个列名前缀匹配
// MultipleColumnPrefixFilter multiFilter = new MultipleColumnPrefixFilter(new byte[][]{});
Scan scan = new Scan();
scan.setFilter(filter);
ResultScanner scanner = table.getScanner(scan);
Map<String,List<Cell>> map = new HashMap<>();
for(Result result:scanner){
map.put(Bytes.toString(result.getRow()),result.listCells());
}
return map;
}
5.4、过滤器集合，多个过滤器同时按通过策略来过滤
//根据列名范围以及列名前缀过滤数据
public Map<String,List<Cell>> filterByPrefixAndRange(String tableNameString,String colPrefix,
String minCol,String maxCol) throws IOException{
Table table = connection.getTable(TableName.valueOf(tableNameString));
//列名前缀匹配
ColumnPrefixFilter filter = new ColumnPrefixFilter(Bytes.toBytes(colPrefix));
//列名范围扫描，上下限范围包括
ColumnRangeFilter rangeFilter = new ColumnRangeFilter(Bytes.toBytes(minCol),true,
Bytes.toBytes(maxCol),true);
FilterList filterList = new FilterList(FilterList.Operator.MUST_PASS_ALL);
filterList.addFilter(filter);
filterList.addFilter(rangeFilter);
Scan scan = new Scan();
scan.setFilter(filterList);
ResultScanner scanner = table.getScanner(scan);
Map<String,List<Cell>> map = new HashMap<>();
for(Result result:scanner){
map.put(Bytes.toString(result.getRow()),result.listCells());
}
return map;
}
6、过滤器介绍
6.1、比较操作，如等于、大于、小于
public enum CompareOperator {
// Keeps same names as the enums over in filter's CompareOp intentionally.
// The convertion of operator to protobuf representation is via a name comparison.
/** less than */
LESS,
/** less than or equal to */
LESS_OR_EQUAL,
/** equals */
EQUAL,
/** not equal */
NOT_EQUAL,
/** greater than or equal to */
GREATER_OR_EQUAL,
/** greater than */
GREATER,
/** no operation */
NO_OP,
}
6.2、比较器，主要是继承ByteArrayComparable的类
RegexStringComparator 支持正则表达式的值比较
Scan scan = new Scan();
RegexStringComparator comp = new RegexStringComparator("you."); // 以 you 开头的字符串
SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes("family"), Bytes.toBytes("qualifier"), CompareOp.EQUAL, comp);
scan.setFilter(filter);
SubStringComparator 用于判断一个子串是否存在于值中，并且不区分大小写。
Scan scan = new Scan();
SubstringComparator comp = new SubstringComparator("substr"); // 查找包含的字符串
SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes("family"), Bytes.toBytes("qualifier"), CompareOp.EQUAL, comp);
scan.setFilter(filter);
BinaryComparator 二进制比较器，不用反序列化直接进行字节比较，比较高效。
Scan scan = new Scan();
BinaryComparator comp = new BinaryComparator(Bytes.toBytes("my hbase"));
ValueFilter filter = new ValueFilter(CompareOp.EQUAL, comp);
scan.setFilter(filter);
BinaryPrefixComparator 前缀二进制比较器。只比较前缀是否相同。
Scan scan = new Scan();
BinaryPrefixComparator comp = new BinaryPrefixComparator(Bytes.toBytes("test")); //
SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes("family"), Bytes.toBytes("qualifier"), CompareOp.EQUAL, comp);
scan.setFilter(filter);
注意：BitComparator、RegexStringComparator、SubStringComparator只能与EQUAL和NOT_EQUAL搭配使用，因为这些比较器的compareTo()方法匹配时返回0，不匹配的时候返回1，如果和LESS或GREATER搭配就会出错。
基于字符串的比较器比基于字节的比较器更慢，也更消耗资源。
6.3、过滤器，部分介绍
行键过滤器
RowFilter 对某一行的过滤。
Scan scan = new Scan();
RowFilter filter = new RowFilter(CompareOp.EQUAL, new BinaryComparator(Bytes.toBytes("row1")));
scan.setFilter(filter);
列族过滤器
FamilyFilter 用于过滤列族（也可以在Scan 过程中通过设定某些列族来实现该功能）
Scan scan = new Scan();
FamilyFilter filter = new FamilyFilter(CompareOp.EQUAL, new BinaryComparator(Bytes.toBytes("info"))); // 列族为 info
scan.setFilter(filter);
列名过滤器
QualifierFilter 列名全匹配
Scan scan = new Scan();
QualifierFilter filter = new QualifierFilter(CompareOp.EQUAL, new BinaryComparator(Bytes.toBytes("username"))); // 列名为 username
scan.setFilter(filter);
ColumnPrefixFilter 用于列名（Qualifier）前缀过滤，即包含某个前缀的所有列名。
Scan scan = new Scan();
ColumnPrefixFilter filter = new ColumnPrefixFilter(Bytes.toBytes("addr")); // 前缀为 addr
scan.setFilter(filter);
MultipleColumnPrefixFilter
MultipleColumnPrefixFilter 与 ColumnPrefixFilter 的行为类似，但可以指定多个列名（Qualifier）前缀。
Scan scan = new Scan();
byte[][] prefixes = new byte[][]{Bytes.toBytes("my-prefix-1"), Bytes.toBytes("my-prefix-2")};
MultipleColumnPrefixFilter filter = new MultipleColumnPrefixFilter(prefixes); 、
scan.setFilter(filter);
ColumnRangeFilter 列名范围过滤器可以进行高效的列名内部扫描。关键字：已排序
Scan scan = new Scan();
ColumnRangeFilter filter = new ColumnRangeFilter(Bytes.toBytes("minColumn"), true, Bytes.toBytes("maxColumn"), false);
scan.setFilter(filter);
DependentColumnFilter 尝试找到该列所在的每一行，并返回该行具有相同时间戳的全部键值对。
Scan scan = new Scan();
DependentColumnFilter filter = new DependentColumnFilter(Bytes.toBytes("family"), Bytes.toBytes("qualifier"));
scan.setFilter(filter);
列值过滤器
SingleColumnValueFilter 列值比较
列族 info 下的列 username的列值和字符串 "admin" 相等的数据 :
Scan scan = new Scan();
SingleColumnValueFilter filter = new SingleColumnValueFilter(Bytes.toBytes("info"), Bytes.toBytes("username"), CompareOp.EQUAL, Bytes.toBytes("admin"));
scan.setFilter(filter);
6.4、代码：
