我有一个 HBase 表(来自 java),我想通过键列表查询表。我做了以下,但它不工作。
mFilterFeatureIt = mFeatureSet.iterator();
FilterList filterList=new FilterList(FilterList.Operator.MUST_PASS_ONE);
while (mFilterFeatureIt.hasNext()) {
long myfeatureId = mFilterFeatureIt.next();
System.out.println("FeatureId:"+myfeatureId+" , ");
RowFilter filter = new RowFilter(CompareOp.EQUAL,new BinaryComparator(Bytes.toBytes(myfeatureId)) );
filterList.addFilter(filter);
}
outputMap = HbaseUtils.getHbaseData("mytable", filterList);
System.out.println("Size of outputMap map:"+ outputMap.szie());
public static Map<String, Map<String, String>> getHbaseData(String table, FilterList filter) {
Map<String, Map<String, String>> data = new HashMap<String, Map<String, String>>();
HTable htable = null;
try {
htable = new HTable(HTableConfiguration.getHTableConfiguration(),table);
Scan scan = new Scan();
scan.setFilter(filter);
ResultScanner resultScanner = htable.getScanner(scan);
Iterator<Result> results = resultScanner.iterator();
while (results.hasNext()) {
Result result = results.next();
String rowId = Bytes.toString(result.getRow());
List<KeyValue> columns = result.list();
if (null != columns) {
HashMap<String, String> colData = new HashMap<String, String>();
for (KeyValue column : columns) {
colData.put(Bytes.toString(column.getFamily()) + ":"+ Bytes.toString(column.getQualifier()),Bytes.toString(column.getValue()));
}
data.put(rowId, colData);
}
}
} catch (IOException e) {
e.printStackTrace();
} finally {
if (htable != null)
try {
htable.close();
} catch (IOException e) {
e.printStackTrace();
}
}
return data;
}
FeatureId:80515900 , FeatureId:80515901 , FeatureId:80515902 ,
outputMap 地图的大小:0
我看到功能 id 的值是我想要的,但即使密钥存在于 hbase 表中,我也总是得到上述输出。谁能告诉我我做错了什么?
编辑:我在上面也发布了我的 hbase util 方法的代码,以便您可以指出那里的任何错误。
我正在尝试做一个与select * FROM mytable where featureId in (80515900, 80515901, 80515902)
我的想法等效的 SQL,以在 HBase 中实现相同的目的是创建一个过滤器列表,其中每个 featureId 都有一个过滤器。那是对的吗 ?
这是我表的内容
scan 'mytable', {COLUMNS => ['sample:tag_count'] }
80515900 column=sample:tag_count, timestamp=1339304052748, value=4
80515901 column=sample:tag_count, timestamp=1339304052748, value=0
80515902 column=sample:tag_count, timestamp=1339304052748, value=3
80515903 column=sample:tag_count, timestamp=1339304052748, value=1
80515904 column=sample:tag_count, timestamp=1339304052748, value=2