DDL(创建及删除表格) 如何在Hbase中创建表格以及删除表格。可通过Java和Hbase Shell两种方法实现。 创建表格 HBase中表格的创建是通过对操作HBaseAdmin这一对象使其调用createTable()这一方法来实现。 其中HTableDescriptor描述了表的schema,可在其上通过
DDL(创建及删除表格)
如何在Hbase中创建表格以及删除表格。可通过Java和Hbase Shell两种方法实现。
创建表格
HBase中表格的创建是通过对操作HBaseAdmin这一对象使其调用createTable()这一方法来实现。
其中HTableDescriptor描述了表的schema,可在其上通过addFamily()这一方法增加列族。
以下Java代码实现了建立一张简易的Hbase表格‘table1’,该表有两个列族,分别为f1和f2。
<code>public class createTable{ private static Configuration config; private static HBaseAdmin ha; public static void main(String[] args){ try{ config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); ha = new HBaseAdmin(config); //create table descriptor String tableName = "table1"; HTableDescriptor htd = new HTableDescriptor(Bytes.toBytes(tableName)); //create and configure column families HColumnDescriptor hcd1 = new HColumnDescriptor(Bytes.toBytes("family1")); hcd1.setBlocksize(65536); hcd1.setMaxVersions(1); hcd1.setBloomFilterType(BloomType.ROW); hcd1.setCompressionType(Algorithm.SNAPPY); hcd1.setDataBlockEncoding(DataBlockEncoding.PREFIX); hcd1.setTimeToLive(36000); hcd1.setInMemory(false); HColumnDescriptor hcd2 = new HColumnDescriptor(Bytes.toBytes("family2")); hcd2.setBlocksize(65536); hcd2.setMaxVersions(1); hcd2.setBloomFilterType(BloomType.ROW); hcd2.setCompressionType(Algorithm.SNAPPY); hcd2.setDataBlockEncoding(DataBlockEncoding.PREFIX); hcd2.setTimeToLive(36000); hcd2.setInMemory(false); //add column families to table descriptor htd.addFamily(hcd1); htd.addFamily(hcd2); //create table ha.createTable(htd); System.out.println("Hbase table created."); }catch (TableExistsException e){ System.out.println("ERROR: attempting to create existing table!"); }catch (IOException e){ e.printStackTrace(); }finally{ try{ ha.close(); }catch(IOException e){ e.printStackTrace(); } } } } </code>
在Hbase Shell中,创建表格功能由create ‘Hbase表名’,[‘列族名’...]来实现。
例如,create ‘table1’,‘family1’,‘family2’同样可创建上述表格。
删除表格
删除表也是通过HBaseAdmin来操作,删除表之前首先要disable表。这是一个比较耗时的操作,所以不建议频繁删除表。
以下Java代码实现了对表格“table1”的删除操作:
<code>public class deleteTable{ private static Configuration config; private static HBaseAdmin ha; public static void main(String[] args){ try{ config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); ha = new HBaseAdmin(config); String tableName = "table1"; //Only an existing table can be dropped if (ha.tableExists(tableName)){ //read&write denied ha.disableTable(tableName); ha.deleteTable(tableName); System.out.println("Hbase table dropped!"); } }catch(IOException e){ e.printStackTrace(); }finally{ try{ ha.close(); }catch(IOException e){ e.printStackTrace(); } } } } </code>
在Hbase Shell中,删除表格功能由drop ‘Hbase表名’来实现。
例如,先disable ‘table1’再drop ‘table1’同样可删除上述表格。
数据插入
在Java操作中,put方法被用做插入数据。
put方法可以传递单个Put对象: public void put(Put put) throws IOException,也可以对很多Put对象进行批量插入: public void put(List puts) throws IOException
以下Java代码实现了对表格"table1"的批量数据插入操作。插入数据后,表格有10000行,列族“family1”,“family2”中都包含“q1”,“q2”两个列,其中列族“family1”储存整型数据(int),列族“family2”储存字符串(string)。
ATTENTION:虽然Hbase支持多种类型储存,但为了应用高性能优化的hbase,表格值的储存类型建议一致使用为String。如上例所示,“family1:q1”中原为整数类型,须转制成string后再录入表中
<code>public class insertTable{ private static Configuration config; public static void main(String[] args) throws IOException{ config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); String tableName = "table1"; HTable table = new HTable(config, tableName); //set AutoFlush table.setAutoFlush(true); int count = 10000; String familyName1 = "family1"; String familyName2 = "family2"; String qualifier1 = "q1"; String qualifier2 = "q2"; //data to be inserted String[] f1q1 = new String[count]; String[] f1q2 = new String[count]; String[] f2q1 = new String[count]; String[] f2q2 = new String[count]; for(int i = 0; i </code>
在Hbase Shell中,单条数据插入功能由put ‘Hbase表名’,‘rowKey’,‘列族名:列名’,‘数据值’来实现。
数据查询
Hbase表格的数据查询可分为单条查询与批量查询。
单条查询
单条查询是通过匹配rowkey在表格中查询某一行的数据。在Java中可通过get()这一方法来实现。
下列Java代码实现了在表格“table1”中取出指定rowkey一行的所有列的数据:
<code>public class getFromTable{ private static Configuration config; public static void main(String[] args) throws IOException{ String tableName = "table1"; config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); HTable table = new HTable(config, tableName); Get get = new Get(Bytes.toBytes("Row01230")); //add target columns for get get.addColumn(Bytes.toBytes("family1"), Bytes.toBytes("q1")); get.addColumn(Bytes.toBytes("family1"), Bytes.toBytes("q2")); get.addColumn(Bytes.toBytes("family2"), Bytes.toBytes("q1")); get.addColumn(Bytes.toBytes("family2"), Bytes.toBytes("q2")); Result result = table.get(get); //get results byte[] rowKey = result.getRow(); byte[] val1 = result.getValue(Bytes.toBytes("family1"), Bytes.toBytes("q1")); byte[] val2 = result.getValue(Bytes.toBytes("family1"),Bytes.toBytes("q2")); byte[] val3 = result.getValue(Bytes.toBytes("family2"), Bytes.toBytes("q1")); byte[] val4 = result.getValue(Bytes.toBytes("family2"), Bytes.toBytes("q2")); System.out.println("Row key: " + Bytes.toString(rowKey)); System.out.println("value1: " + Bytes.toString(val1)); System.out.println("value2: " + Bytes.toString(val2)); System.out.println("value3: " + Bytes.toString(val3)); System.out.println("value4: " + Bytes.toString(val4)); table.close(); } } </code>
在Hbase Shell中,单条数据查找功能由get ‘Hbase表名’,‘rowKey’,‘列族名:列名’来实现。
批量查询
批量查询是通过制定一段rowkey的范围来查询。可通过Java中getScanner()这一方法来实现。
下列Java代码实现了在表格“table1”中取出指定一段rowkey范围的所有列的数据:
<code>public class scanFromTable { private static Configuration config; public static void main(String[] args) throws IOException{ config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); String tableName = "table1"; HTable table = new HTable(config, tableName); //Scan according to rowkey range Scan scan = new Scan(); //set starting row(included), if not set, start from the first row scan.setStartRow(Bytes.toBytes("Row01000")); //set stopping row(excluded), if not set, stop at the last row scan.setStopRow(Bytes.toBytes("Row01100")); //specify columns to scan, if not specified, return all columns; scan.addColumn(Bytes.toBytes("family1"), Bytes.toBytes("q1")); scan.addColumn(Bytes.toBytes("family1"), Bytes.toBytes("q2")); scan.addColumn(Bytes.toBytes("family2"), Bytes.toBytes("q1")); scan.addColumn(Bytes.toBytes("family2"), Bytes.toBytes("q2")); //specify maximum versions for one cell, if called without arguments, get all versions, if not called, get only the latest version scan.setMaxVersions(); //specify maximum number of cells to avoid OutOfMemory error caused by huge amount of data in a single row scan.setBatch(10000); ResultScanner rs = table.getScanner(scan); for(Result r:rs){ byte[] rowKey = r.getRow(); byte[] val1 = r.getValue(Bytes.toBytes("family1"), Bytes.toBytes("q1")); byte[] val2 = r.getValue(Bytes.toBytes("family1"), Bytes.toBytes("q2")); byte[] val3 = r.getValue(Bytes.toBytes("family2"), Bytes.toBytes("q1")); byte[] val4 = r.getValue(Bytes.toBytes("family2"), Bytes.toBytes("q2")); System.out.print(Bytes.toString(rowKey)+": "); System.out.print(Bytes.toString(val1)+" "); System.out.print(Bytes.toString(val2)+" "); System.out.print(Bytes.toString(val3)+" "); System.out.println(Bytes.toString(val4)); } rs.close(); table.close(); } } </code>
在Hbase Shell中,批量数据查找功能由scan ‘Hbase表名’,{COLUMNS=>‘列族名:列名’,STARTROW=>‘起始rowkey’,STOPROW=>‘终止rowkey’}来实现。
利用过滤器筛选
过滤器是在Hbase服务器端上执行筛选操作,可以应用到行键(RowFilter),列限定符(QualifierFilter)以及数据值(ValueFilter)。
这里列举了两个常用的过滤器:RowFilter和SingleColumnValueFilter。
RowFilter
RowFilter通过行键(rowkey)来筛选数据。
其中BinaryComparator直接比较两个byte array,可选的比较符(CompareOp)有EQUAL,NOT_EQUAL,GREATER,GREATER_OR_EQUAL,LESS,LESS_OR_EQUAL。
<code>public class rowFilter{ public static void main(String[] args) throws IOException{ String tableName = "table1"; Configuration config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); HTable table = new HTable(config, tableName); Scan scan = new Scan(); scan.addColumn(Bytes.toBytes("family1"), Bytes.toBytes("q1")); Filter filter = new RowFilter(CompareFilter.CompareOp.EQUAL, new BinaryComparator(Bytes.toBytes("Row01234"))); scan.setFilter(filter); ResultScanner scanner = table.getScanner(scan); for(Result res:scanner){ byte[] value = res.getValue(Bytes.toBytes("family1"),Bytes.toBytes("q1")); System.out.println(new String(res.getRow())+" value is: "+Bytes.toString(value)); } scanner.close(); table.close(); } } </code>
SingleColumnValueFilter
SingleColumnValueFilter对某一具体列的值进行筛选。
其中SubstringComparator检查给定的字符串是否是列值的子字符串,可选的比较符(CompareOp)有EQUAL和NOT_EQUAL。
<code>public class singleColumnValueFilter{ public static void main(String[] args) throws IOException{ Configuration config = HBaseConfiguration.create(); config.addResource("core-site.xml"); config.addResource("hdfs-site.xml"); config.addResource("yarn-site.xml"); config.addResource("mapred-site.xml"); String tableName = "table1"; HTable table = new HTable(config,tableName); SingleColumnValueFilter filter = new SingleColumnValueFilter( Bytes.toBytes("family2"), Bytes.toBytes("q1"), CompareFilter.CompareOp.NOT_EQUAL, new SubstringComparator("45")); //when setting setFilterIfMissing(true), rows with "null" values are filtered filter.setFilterIfMissing(true); Scan scan = new Scan(); scan.setFilter(filter); ResultScanner scanner = table.getScanner(scan); for (Result res:scanner){ byte[] val = res.getValue(Bytes.toBytes("family1"), Bytes.toBytes("q1")); System.out.println(new String(res.getRow())); System.out.println("value: " + Bytes.toString(val)); } scanner.close(); table.close(); } } </code>
原文地址:hbase Java API操作实例, 感谢原作者分享。

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