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Tablestore:Terms query

Last Updated:Apr 29, 2026

A terms query returns rows where a column value exactly matches at least one of the specified terms — the equivalent of the SQL IN operator. Unlike a term query, a terms query accepts multiple match values.

Prerequisites

Parameters

Parameter

Description

query_type

The query type. Set this parameter to TermsQuery.

field_name

The name of the column to query.

terms

The list of terms to match against the column value.

A row is returned if its column value exactly matches at least one term in the list.

table_name

The name of the data table.

index_name

The name of the search index.

limit

The maximum number of rows to return.

Set this parameter to 0 to count matching rows without returning their data.

get_total_count

Whether to return the total number of rows that match the query conditions. The default value is false.

Setting this to true degrades query performance.

columns_To_get

The columns to return for each matching row. Specify return_type and, optionally, column_names.

  • ColumnReturnType.SPECIFIED: return only the columns listed in column_names.

  • ColumnReturnType.ALL: return all columns.

  • ColumnReturnType.NONE: return only primary key columns.

Examples

The following examples query rows where the Col_Keyword column exactly matches one of key000, key100, key888, key999, key908, or key1000.

Note: Setting get_total_count to true degrades query performance. Only enable this when you need an exact match count.
  • SDK for Python V5.2.1 and later

    SDK for Python V5.2.1 and later returns a SearchResponse object by default.

    query = TermsQuery('Col_Keyword', ['key000', 'key100', 'key888', 'key999', 'key908', 'key1000'])
    search_response = client.search(
        '<TABLE_NAME>', '<SEARCH_INDEX_NAME>',
        SearchQuery(query, limit=100, get_total_count=True),
        ColumnsToGet(return_type=ColumnReturnType.ALL)
    )
    print('request_id : %s' % search_response.request_id)
    print('is_all_succeed : %s' % search_response.is_all_succeed)
    print('total_count : %s' % search_response.total_count)
    print('rows : %s' % search_response.rows)
    
    # For deep paging, use next_token — it has no limit on paging depth.
    # all_rows = []
    # next_token = None
    # # First page
    # search_response = client.search(
    #     '<TABLE_NAME>', '<SEARCH_INDEX_NAME>',
    #     SearchQuery(query, next_token=next_token, limit=100, get_total_count=True),
    #     columns_to_get=ColumnsToGet(return_type=ColumnReturnType.ALL))
    # all_rows.extend(search_response.rows)
    #
    # # Subsequent pages
    # while search_response.next_token:
    #     search_response = client.search(
    #         '<TABLE_NAME>', '<SEARCH_INDEX_NAME>',
    #         SearchQuery(query, next_token=search_response.next_token, limit=100, get_total_count=True),
    #         columns_to_get=ColumnsToGet(return_type=ColumnReturnType.ALL))
    #     all_rows.extend(search_response.rows)
    # print('Total rows:%s' % len(all_rows))

    To get results as a tuple instead:

    query = TermsQuery('Col_Keyword', ['key000', 'key100', 'key888', 'key999', 'key908', 'key1000'])
    rows, next_token, total_count, is_all_succeed, agg_results, group_by_results = client.search(
        '<TABLE_NAME>', '<SEARCH_INDEX_NAME>',
        SearchQuery(query, limit=100, get_total_count=True),
        ColumnsToGet(return_type=ColumnReturnType.ALL)
    ).v1_response()
  • SDK for Python earlier than V5.2.1

    SDK for Python earlier than V5.2.1 returns results as a tuple by default.

    query = TermsQuery('Col_Keyword', ['key000', 'key100', 'key888', 'key999', 'key908', 'key1000'])
    rows, next_token, total_count, is_all_succeed = client.search(
        '<TABLE_NAME>', '<SEARCH_INDEX_NAME>',
        SearchQuery(query, limit=100, get_total_count=True),
        ColumnsToGet(return_type=ColumnReturnType.ALL)
    )

FAQ

References

  • When you use a search index to query data, you can use the following query methods: term query, terms query, match all query, match query, match phrase query, prefix query, range query, wildcard query, geo query, Boolean query, KNN vector query, nested query, and exists query. You can use the query methods provided by the search index to query data from multiple dimensions based on your business requirements.

    You can sort or paginate rows that meet the query conditions by using the sorting and paging features. For more information, see Sorting and paging.

    You can use the collapse (distinct) feature to collapse the result set based on a specific column. This way, data of the specified type appears only once in the query results. For more information, see Collapse (distinct).

  • If you want to analyze data in a data table, you can use the aggregation feature of the Search operation or execute SQL statements. For example, you can obtain the minimum and maximum values, sum, and total number of rows. For more information, see Aggregation and SQL query.

  • If you want to obtain all rows that meet the query conditions without the need to sort the rows, you can call the ParallelScan and ComputeSplits operations to use the parallel scan feature. For more information, see Parallel scan.