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
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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 |
|
field_name |
The name of the column to query. |
|
prefix |
The prefix to match. If the column is a TEXT column, the column is tokenized first. A row matches when at least one token contains the specified prefix. |
|
query |
The query type. Set this parameter to |
|
table_name |
The name of the data table. |
|
index_name |
The name of the search index. |
|
limit |
The maximum number of rows to return in a single query. To count matching rows without retrieving data, set this parameter to |
|
get_total_count |
Specifies whether to return the total number of rows that match the query conditions. Default value: Setting this parameter to |
|
columns_to_get |
Controls which columns to return for each matching row. Configure this parameter using the
|
Examples
The following examples show how to query rows whose Col_Keyword column value is prefixed with tablestore.
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Perform a prefix query by using Tablestore SDK for Python V5.2.1 or later
Tablestore SDK for Python V5.2.1 and later returns a
SearchResponseobject by default. The following code shows 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, use next_token to avoid limits on 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))To return results as a tuple instead, call
.v1_response()on the result: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
Tablestore SDK for Python versions earlier than V5.2.1 return results as a tuple by default. The following code shows 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.