试试这个。虽然有点丑,但对我有用。
import org.apache.hadoop.hbase.filter.CompareFilter
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter
import org.apache.hadoop.hbase.filter.SubstringComparator
import org.apache.hadoop.hbase.util.Bytes
scan 't1', { COLUMNS => 'family:qualifier', FILTER =>
SingleColumnValueFilter.new
(Bytes.toBytes('family'),
Bytes.toBytes('qualifier'),
CompareFilter::CompareOp.valueOf('EQUAL'),
SubstringComparator.new('somevalue'))
}
HBase shell 将包含 ~/.irbrc 中的所有内容,因此您可以在其中放入类似的内容(我不是 Ruby 专家,欢迎改进):
# imports like above
def scan_substr(table,family,qualifier,substr,*cols)
scan table, { COLUMNS => cols, FILTER =>
SingleColumnValueFilter.new
(Bytes.toBytes(family), Bytes.toBytes(qualifier),
CompareFilter::CompareOp.valueOf('EQUAL'),
SubstringComparator.new(substr)) }
end
然后你可以在 shell 中说:
scan_substr 't1', 'family', 'qualifier', 'somevalue', 'family:qualifier'
scan 'test', {COLUMNS => ['F'],FILTER => \
"(SingleColumnValueFilter('F','u',=,'regexstring:http:.*pdf',true,true)) AND \
(SingleColumnValueFilter('F','s',=,'binary:2',true,true))"}
更多信息可以在这里找到。请注意,多个示例位于随附的
Filter Language.docx
文件中。
使用
scan
的FILTER参数,如使用帮助所示:
hbase(main):002:0> scan
ERROR: wrong number of arguments (0 for 1)
Here is some help for this command:
Scan a table; pass table name and optionally a dictionary of scanner
specifications. Scanner specifications may include one or more of:
TIMERANGE, FILTER, LIMIT, STARTROW, STOPROW, TIMESTAMP, MAXLENGTH,
or COLUMNS. If no columns are specified, all columns will be scanned.
To scan all members of a column family, leave the qualifier empty as in
'col_family:'.
Some examples:
hbase> scan '.META.'
hbase> scan '.META.', {COLUMNS => 'info:regioninfo'}
hbase> scan 't1', {COLUMNS => ['c1', 'c2'], LIMIT => 10, STARTROW => 'xyz'}
hbase> scan 't1', {FILTER => org.apache.hadoop.hbase.filter.ColumnPaginationFilter.new(1, 0)}
hbase> scan 't1', {COLUMNS => 'c1', TIMERANGE => [1303668804, 1303668904]}
For experts, there is an additional option -- CACHE_BLOCKS -- which
switches block caching for the scanner on (true) or off (false). By
default it is enabled. Examples:
hbase> scan 't1', {COLUMNS => ['c1', 'c2'], CACHE_BLOCKS => false}
Scan scan = new Scan();
FilterList list = new FilterList(FilterList.Operator.MUST_PASS_ALL);
//in case you have multiple SingleColumnValueFilters,
you would want the row to pass MUST_PASS_ALL conditions
or MUST_PASS_ONE condition.
SingleColumnValueFilter filter_by_name = new SingleColumnValueFilter(
Bytes.toBytes("SOME COLUMN FAMILY" ),
Bytes.toBytes("SOME COLUMN NAME"),
CompareOp.EQUAL,
Bytes.toBytes("SOME VALUE"));
filter_by_name.setFilterIfMissing(true);
//if you don't want the rows that have the column missing.
Remember that adding the column filter doesn't mean that the
rows that don't have the column will not be put into the
result set. They will be, if you don't include this statement.
list.addFilter(filter_by_name);
scan.setFilter(list);
其中一个过滤器是Valuefilter,可用于过滤所有列值。
hbase(main):067:0> scan 'dummytable', {FILTER => "ValueFilter(=,'binary:2016-01-26')"}
binary 是滤波器中使用的比较器之一。您可以根据您想要执行的操作在过滤器中使用不同的比较器。
您可以参考以下网址:http://www.hadooptpoint.com/filters-in-hbase-shell/。 它提供了有关如何在 HBase Shell 中使用不同过滤器的很好的示例。
在查询末尾添加 setFilterIfMissing(true)
hbase(main):009:0> import org.apache.hadoop.hbase.util.Bytes;
import org.apache.hadoop.hbase.filter.SingleColumnValueFilter;
import org.apache.hadoop.hbase.filter.BinaryComparator;
import org.apache.hadoop.hbase.filter.CompareFilter;
import org.apache.hadoop.hbase.filter. Filter;
scan 'test:test8', { FILTER => SingleColumnValueFilter.new(Bytes.toBytes('account'),
Bytes.toBytes('ACCOUNT_NUMBER'), CompareFilter::CompareOp.valueOf('EQUAL'),
BinaryComparator.new(Bytes.toBytes('0003000587'))).setFilterIfMissing(true)}
您可以在 hbase shell 中使用以下命令来过滤列数据
扫描 'tableName',{ COLUMNS => 'columnName', LIMIT => 1, FILTER => "ValueFilter( =, 'regexstring:customer' )" }