You can perform a prefix query to query data that matches the specified prefix. If the column used to match the prefix condition is a TEXT column, the column is tokenized. A row meets the query conditions when at least one token contains the specified prefix.
Prerequisites
A TableStoreClient instance is initialized. For more information, see Initialize an OTSClient instance.
A data table is created and data is written to the data table. For more information, see Create a data table and Write data.
A search index is created for the data table. For more information, see Create a search index.
Parameters
Parameter | Description |
field_name | The name of the column that you want to query. |
prefix | The prefix. If the column used to match the prefix condition is a TEXT column, the column is tokenized. A row meets the query conditions when at least one token contains the specified prefix. |
query | The type of the query. Set this parameter to PrefixQuery. |
table_name | The name of the data table. |
index_name | The name of the search index. |
limit | The maximum number of rows that you want the current query to return. To query only the number of rows that meet the query conditions without querying specific data of the rows, set this parameter to 0. |
get_total_count | Specifies whether to return the total number of rows that meet the query conditions. The default value of this parameter is false, which specifies that the total number of rows that meet the query conditions is not returned. If you set this parameter to true, the query performance is compromised. |
columns_to_get | Specifies whether to return all columns of each row that meets the query conditions. You can specify the return_type and column_names fields for this parameter.
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Examples
The following examples show how to query the rows whose value of the Col_Keyword column is prefixed with 'tablestore'.
Perform a prefix query by using Tablestore SDK for Python V5.2.1 or later
By default, if you use Tablestore SDK for Python V5.2.1 or later to perform a prefix query, a SearchResponse object is returned. The following code provides a sample request:
query = PrefixQuery('Col_Keyword', 'tablestore') 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) # # If deep paging is required, we recommend that you configure the next_token parameter because this method has no limits on the paging depth. # all_rows = [] # next_token = None # # first round # 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) # # # loop # 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))
You can use the following sample request to return results of the Tuple type:
query = PrefixQuery('Col_Keyword', 'tablestore') 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()
Perform a prefix query by using Tablestore SDK for Python of a version earlier than 5.2.1
If you use a version of Tablestore SDK for Python that is earlier than V5.2.1 to perform a prefix query, results of the TUPLE type are returned by default. The following sample code provides a sample request:
query = PrefixQuery('Col_Keyword', 'tablestore') 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.