Bigtable Row Filters

It is possible to use a RowFilter when adding mutations to a ConditionalRow and when reading row data with read_row() read_rows().

As laid out in the RowFilter definition, the following basic filters are provided:

• SinkFilter
• PassAllFilter
• BlockAllFilter
• RowKeyRegexFilter
• RowSampleFilter
• FamilyNameRegexFilter
• ColumnQualifierRegexFilter
• TimestampRangeFilter
• ColumnRangeFilter
• ValueRegexFilter
• ValueRangeFilter
• CellsRowOffsetFilter
• CellsRowLimitFilter
• CellsColumnLimitFilter
• StripValueTransformerFilter
• ApplyLabelFilter

In addition, these filters can be combined into composite filters with

• RowFilterChain
• RowFilterUnion
• ConditionalRowFilter

These rules can be nested arbitrarily, with a basic filter at the lowest level. For example:

# Filter in a specified column (matching any column family).
col1_filter = ColumnQualifierRegexFilter(b'columnbia')

# Create a filter to label results.
label1 = u'label-red'
label1_filter = ApplyLabelFilter(label1)

# Combine the filters to label all the cells in columnbia.
chain1 = RowFilterChain(filters=[col1_filter, label1_filter])

# Create a similar filter to label cells blue.
col2_filter = ColumnQualifierRegexFilter(b'columnseeya')
label2 = u'label-blue'
label2_filter = ApplyLabelFilter(label2)
chain2 = RowFilterChain(filters=[col2_filter, label2_filter])

# Bring our two labeled columns together.
row_filter = RowFilterUnion(filters=[chain1, chain2])

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