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
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An OTSClient instance is initialized. For more information, see Initialize a Tablestore client.
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A data table is created and data is written to the data table. For more information, see Create a data table and Write data.
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A search index is created for the data table. For more information, see Create a search index.
Parameters
|
Parameter |
Description |
|
query_type |
The query type. Set this parameter to |
|
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 |
|
get_total_count |
Whether to return the total number of rows that match the query conditions. The default value is Setting this to |
|
columns_To_get |
The columns to return for each matching row. Specify
|
Examples
The following examples query rows where the Col_Keyword column exactly matches one of key000, key100, key888, key999, key908, or key1000.
Note: Settingget_total_counttotruedegrades query performance. Only enable this when you need an exact match count.
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SDK for Python V5.2.1 and later
SDK for Python V5.2.1 and later returns a
SearchResponseobject 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.