參數基礎
有兩個參數類在各類Filter中經常出現，統一介紹下：
（1）比較運算符 CompareFilter.CompareOp
比較運算符用於定義比較關係，可以有以下幾類值供選擇：
EQUAL 相等
GREATER 大於
GREATER_OR_EQUAL 大於等於
LESS 小於
LESS_OR_EQUAL 小於等於
NOT_EQUAL 不等於
（2）比較器 ByteArrayComparable
通過比較器可以實現多樣化目標匹配效果，比較器有以下子類可以使用：
BinaryComparator 匹配完整字節數組
BinaryPrefixComparator 匹配字節數組前綴
BitComparator
NullComparator
RegexStringComparator 正則表達式匹配
SubstringComparator 子串匹配
1，FilterList
FilterList 代表一個過濾器鏈，它可以包含一組即將應用於目標數據集的過濾器，過濾器間具有“與” FilterList.Operator.MUST_PASS_ALL 和“或” FilterList.Operator.MUST_PASS_ONE 關係。
官網實例代碼，兩個“或”關係的過濾器的寫法：
FilterList list = new FilterList(FilterList.Operator.MUST_PASS_ONE); //數據只要滿足一組過濾器中的一個就可以
SingleColumnValueFilter filter1 = new SingleColumnValueFilter(cf,column,CompareOp.EQUAL,Bytes.toBytes("my value"));
list.add(filter1);
SingleColumnValueFilter filter2 = new SingleColumnValueFilter(cf,column,CompareOp.EQUAL,Bytes.toBytes("my other value"));
list.add(filter2);
Scan scan = new Scan();
scan.setFilter(list);
2，列值過濾器--SingleColumnValueFilter
SingleColumnValueFilter 用於測試列值相等 (CompareOp.EQUAL ), 不等 (CompareOp.NOT_EQUAL),或單側範圍 (e.g., CompareOp.GREATER)。
構造函數：
（1）比較的關鍵字是一個字符數組
SingleColumnValueFilter(byte[] family, byte[] qualifier, CompareFilter.CompareOp compareOp, byte[] value)
（2）比較的關鍵字是一個比較器（比較器下一小節做介紹）
SingleColumnValueFilter(byte[] family, byte[] qualifier, CompareFilter.CompareOp compareOp, ByteArrayComparable comparator)
注意：根據列的值來決定這一行數據是否返回，落腳點在行，而不是列。我們可以設置filter.setFilterIfMissing(true);如果爲true，當這一列不存在時，不會返回，如果爲false，當這一列不存在時，會返回所有的列信息
測試表user內容如下：
java代碼測試：
Table table = connection.getTable(TableName.valueOf("user"));
SingleColumnValueFilter scvf= new SingleColumnValueFilter(Bytes.toBytes("account"), Bytes.toBytes("name"),
CompareOp.EQUAL,"zhangsan".getBytes());
scvf.setFilterIfMissing(true); //默認爲false， 沒有此列的數據也會返回 ，爲true則只返回name=lisi的數據
Scan scan = new Scan();
scan.setFilter(scvf);
ResultScanner resultScanner = table.getScanner(scan);
for (Result result : resultScanner) {
List<Cell> cells= result.listCells();
for (Cell cell : cells) {
String row = Bytes.toString(result.getRow());
String family1 = Bytes.toString(CellUtil.cloneFamily(cell));
String qualifier = Bytes.toString(CellUtil.cloneQualifier(cell));
String value = Bytes.toString(CellUtil.cloneValue(cell));
System.out.println("[row:"+row+"],[family:"+family1+"],[qualifier:"+qualifier+"]"
+ ",[value:"+value+"],[time:"+cell.getTimestamp()+"]");
}
}
如果setFilterIfMissing(true), 有匹配只會返回當前列所在的行數據，基於行的數據 country 也返回了，因爲他麼你的rowkey是相同的
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
如果setFilterIfMissing（false），有匹配的列的值相同會返回，沒有此列的 name的也會返回，， 不匹配的name則不會返回。
下面 紅色是匹配列內容的會返回，其他的不是account：name列也會返回，， name=lisi的不會返回，因爲不匹配。
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230],[time:1495556647872]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236],[time:1495556648013]
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔],[time:1495556648017]
[row:lisi_1495527850136],[family:address],[qualifier:province],[value:shanghai],[time:1495556648041]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21],[time:1495556648045]
[row:lisi_1495527850154],[family:info],[qualifier:sex],[value:女],[time:1495556648056]
[row:lisi_1495527850159],[family:userid],[qualifier:id],[value:002],[time:1495556648060]
[row:wangwu_1495595824517],[family:userid],[qualifier:id],[value:009],[time:1495624624131]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898],[time:1495636370056]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong],[time:1495556648855]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男],[time:1495556648983]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001],[time:1495556648996]
3. 鍵值元數據
由於HBase 採用鍵值對保存內部數據，鍵值元數據過濾器評估一行的鍵(ColumnFamily：Qualifiers)是否存在
3.1. 基於列族過濾數據的FamilyFilter
構造函數：
FamilyFilter(CompareFilter.CompareOp familyCompareOp, ByteArrayComparable familyComparator)
代碼如下：
public static ResultScanner getDataFamilyFilter(String tableName,String family) throws IOException{
Table table = connection.getTable(TableName.valueOf("user"));
FamilyFilter ff = new FamilyFilter(CompareOp.EQUAL ,
new BinaryComparator(Bytes.toBytes("account"))); //表中不存在account列族，過濾結果爲空
// new BinaryPrefixComparator(value) //匹配字節數組前綴
// new RegexStringComparator(expr) // 正則表達式匹配
// new SubstringComparator(substr)// 子字符串匹配
Scan scan = new Scan();
// 通過scan.addFamily(family) 也可以實現此操作
scan.setFilter(ff);
ResultScanner resultScanner = table.getScanner(scan);
return resultScanner;
}
測試結果：查詢的都是account列簇的內容
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230],[time:1495556647872]
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236],[time:1495556648013]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898],[time:1495636370056]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
3.2. 基於限定符Qualifier（列）過濾數據的QualifierFilter
構造函數：
QualifierFilter(CompareFilter.CompareOp op, ByteArrayComparable qualifierComparator)
Table table = connection.getTable(TableName.valueOf("user"));
QualifierFilter ff = new QualifierFilter(
CompareOp.EQUAL , new BinaryComparator(Bytes.toBytes("name")));
// new BinaryPrefixComparator(value) //匹配字節數組前綴
// new RegexStringComparator(expr) // 正則表達式匹配
// new SubstringComparator(substr)// 子字符串匹配
Scan scan = new Scan();
// 通過scan.addFamily(family) 也可以實現此操作
scan.setFilter(ff);
ResultScanner resultScanner = table.getScanner(scan);
測試結果：只返回 name 的列內容
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
3.3. 基於列名(即Qualifier)前綴過濾數據的ColumnPrefixFilter （ 該功能用QualifierFilter也能實現 ）
構造函數：
ColumnPrefixFilter(byte[] prefix)
Table table = connection.getTable(TableName.valueOf("user"));
ColumnPrefixFilter ff = new ColumnPrefixFilter(Bytes.toBytes("name"));
Scan scan = new Scan();
// 通過QualifierFilter的 newBinaryPrefixComparator也可以實現
scan.setFilter(ff);
ResultScanner resultScanner = table.getScanner(scan);
返回結果：
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
3.4. 基於多個列名(即Qualifier)前綴過濾數據的MultipleColumnPrefixFilter
MultipleColumnPrefixFilter 和 ColumnPrefixFilter 行爲差不多，但可以指定多個前綴
byte[][] prefixes = new byte[][] {Bytes.toBytes("name"), Bytes.toBytes("age")};
//返回所有行中以name或者age打頭的列的數據
MultipleColumnPrefixFilter ff = new MultipleColumnPrefixFilter(prefixes);
Scan scan = new Scan();
scan.setFilter(ff);
ResultScanner rs = table.getScanner(scan);
結果：
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21],[time:1495556648045]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
3.5. 基於列範圍過濾數據ColumnRangeFilter
構造函數：
ColumnRangeFilter(byte[] minColumn, boolean minColumnInclusive, byte[] maxColumn, boolean maxColumnInclusive)
參數解釋：
minColumn - 列範圍的最小值，如果爲空，則沒有下限；
minColumnInclusive - 列範圍是否包含minColumn ；
maxColumn - 列範圍最大值，如果爲空，則沒有上限；
maxColumnInclusive - 列範圍是否包含maxColumn 。
代碼：
Table table = connection.getTable(TableName.valueOf("user"));
byte[] startColumn = Bytes.toBytes("a");
byte[] endColumn = Bytes.toBytes("d");
//返回所有列中從a到d打頭的範圍的數據，
ColumnRangeFilter ff = new ColumnRangeFilter(startColumn, true, endColumn, true);
Scan scan = new Scan();
scan.setFilter(ff);
ResultScanner rs = table.getScanner(scan);
結果：返回列名開頭是a 到 d的所有列數據
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔],[time:1495556648017]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21],[time:1495556648045]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
4. RowKey
當需要根據行鍵特徵查找一個範圍的行數據時，使用Scan的startRow和stopRow會更高效，但是，startRow和stopRow只能匹配行鍵的開始字符，而不能匹配中間包含的字符：
byte[] startColumn = Bytes.toBytes("azha");
byte[] endColumn = Bytes.toBytes("dddf");
Scan scan = new Scan(startColumn,endColumn);
當需要針對行鍵進行更復雜的過濾時，可以使用RowFilter：
構造函數：
RowFilter(CompareFilter.CompareOp rowCompareOp, ByteArrayComparable rowComparator)
代碼：
Table table = connection.getTable(TableName.valueOf("user"));
RowFilter rf = new RowFilter(CompareOp.EQUAL ,
new SubstringComparator("zhangsan"));
// new BinaryPrefixComparator(value) //匹配字節數組前綴
// new RegexStringComparator(expr) // 正則表達式匹配
// new SubstringComparator(substr)// 子字符串匹配
Scan scan = new Scan();
scan.setFilter(rf);
ResultScanner rs = table.getScanner(scan);
結果：
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898],[time:1495636370056]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong],[time:1495556648855]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男],[time:1495556648983]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001],[time:1495556648996]
5.PageFilter
指定頁面行數，返回對應行數的結果集。
需要注意的是，該過濾器並不能保證返回的結果行數小於等於指定的頁面行數，因爲過濾器是分別作用到各個region server的，它只能保證當前region返回的結果行數不超過指定頁面行數。
構造函數：
PageFilter(long pageSize)
代碼：
Table table = connection.getTable(TableName.valueOf("user"));
PageFilter pf = new PageFilter(2L);
Scan scan = new Scan();
scan.setFilter(pf);
scan.setStartRow(Bytes.toBytes("zhangsan_"));
ResultScanner rs = table.getScanner(scan);
結果：返回的結果實際上有四條，因爲這數據來自不同RegionServer,
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898],[time:1495636370056]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan],[time:1495556648729]
6.SkipFilter
根據整行中的每個列來做過濾，只要存在一列不滿足條件，整行都被過濾掉。
例如，如果一行中的所有列代表的是不同物品的重量，則真實場景下這些數值都必須大於零，我們希望將那些包含任意列值爲0的行都過濾掉。
在這個情況下，我們結合ValueFilter和SkipFilter共同實現該目的：
scan.setFilter(new SkipFilter(new ValueFilter(CompareOp.NOT_EQUAL,new BinaryComparator(Bytes.toBytes(0))));
構造函數：
SkipFilter(Filter filter)
代碼：
Table table = connection.getTable(TableName.valueOf("user"));
SkipFilter sf = new SkipFilter(new ValueFilter(CompareOp.NOT_EQUAL,
new BinaryComparator(Bytes.toBytes("zhangsan"))));
Scan scan = new Scan();
scan.setFilter(sf);
ResultScanner rs = table.getScanner(scan);
結果：
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230],[time:1495556647872]
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236],[time:1495556648013]
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔],[time:1495556648017]
[row:lisi_1495527850136],[family:address],[qualifier:province],[value:shanghai],[time:1495556648041]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21],[time:1495556648045]
[row:lisi_1495527850154],[family:info],[qualifier:sex],[value:女],[time:1495556648056]
[row:lisi_1495527850159],[family:userid],[qualifier:id],[value:002],[time:1495556648060]
[row:wangwu_1495595824517],[family:userid],[qualifier:id],[value:009],[time:1495624624131]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898],[time:1495636370056]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong],[time:1495556648855]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男],[time:1495556648983]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001],[time:1495556648996]
和原來數據相比 列值爲name的 zhagnsan的所在行的 rowkey 爲 zhangsan_1495527850824 在上面結果中是過濾了
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230]
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236]
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔]
[row:lisi_1495527850136],[family:address],[qualifier:province],[value:shanghai]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21]
[row:lisi_1495527850154],[family:info],[qualifier:sex],[value:女]
[row:lisi_1495527850159],[family:userid],[qualifier:id],[value:002]
[row:wangwu_1495595824517],[family:userid],[qualifier:id],[value:009]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001]
7. FirstKeyOnlyFilter
該過濾器僅僅返回每一行中的第一個cell的值，可以用於高效的執行行數統計操作。
構造函數：
public FirstKeyOnlyFilter()
代碼
Table table = connection.getTable(TableName.valueOf("user"));
FirstKeyOnlyFilter fkof = new FirstKeyOnlyFilter();
Scan scan = new Scan();
scan.setFilter(fkof);
ResultScanner rs = table.getScanner(scan);
結果： 看着返回數據還沒明白，僅僅返回每一行中的第一個cell的值，可以用於高效的執行行數統計操作。
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230],[time:1495556647872]
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi],[time:1495556647984]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236],[time:1495556648013]
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔],[time:1495556648017]
[row:lisi_1495527850136],[family:address],[qualifier:province],[value:shanghai],[time:1495556648041]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21],[time:1495556648045]
[row:lisi_1495527850154],[family:info],[qualifier:sex],[value:女],[time:1495556648056]
[row:lisi_1495527850159],[family:userid],[qualifier:id],[value:002],[time:1495556648060]
[row:wangwu_1495595824517],[family:userid],[qualifier:id],[value:009],[time:1495624624131]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646],[time:1495556648664]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china],[time:1495636452285]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong],[time:1495556648855]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100],[time:1495556648878]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男],[time:1495556648983]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001],[time:1495556648996]
對比原數據：
[row:lisi_1495527849910],[family:account],[qualifier:idcard],[value:42963319861234561230]
[row:lisi_1495527850081],[family:account],[qualifier:name],[value:lisi]
[row:lisi_1495527850111],[family:account],[qualifier:password],[value:123451231236]
[row:lisi_1495527850114],[family:address],[qualifier:city],[value:黃埔]
[row:lisi_1495527850136],[family:address],[qualifier:province],[value:shanghai]
[row:lisi_1495527850144],[family:info],[qualifier:age],[value:21]
[row:lisi_1495527850154],[family:info],[qualifier:sex],[value:女]
[row:lisi_1495527850159],[family:userid],[qualifier:id],[value:002]
[row:wangwu_1495595824517],[family:userid],[qualifier:id],[value:009]
[row:zhangsan_1495527850759],[family:account],[qualifier:idcard],[value:9897645464646]
[row:zhangsan_1495527850759],[family:account],[qualifier:passport],[value:5689879898]
[row:zhangsan_1495527850824],[family:account],[qualifier:country],[value:china]
[row:zhangsan_1495527850824],[family:account],[qualifier:name],[value:zhangsan]
[row:zhangsan_1495527850951],[family:address],[qualifier:province],[value:guangdong]
[row:zhangsan_1495527850975],[family:info],[qualifier:age],[value:100]
[row:zhangsan_1495527851080],[family:info],[qualifier:sex],[value:男]
[row:zhangsan_1495527851095],[family:userid],[qualifier:id],[value:001]
對比一下明顯，rowkey相同的只會返回第一個rowkey的所在cell數據