Tablestore:Term query

Prerequisites

• An OTSClient instance is initialized. For more information, see Initialize a Tablestore client.

• 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

Examples

The following examples query rows where the Col_Keyword field exactly matches "tablestore".

• Tablestore SDK for Python V5.2.1 or later

  SDK for Python V5.2.1 and later returns a SearchResponse object by default. The following example shows a basic term query:

  query = TermQuery('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)
  
  # For deep pagination, use next_token — it has no limit on pagination 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 get results as a Tuple instead, call .v1_response():

  query = TermQuery('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()

• Tablestore SDK for Python earlier than 5.2.1

  SDK for Python versions earlier than 5.2.1 return results as a Tuple by default:

  query = TermQuery('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

• What do I do if no data can be found by calling the Search operation?

• How do I increase the value of the limit parameter to 1000 when I call the Search operation of the search index feature to query data?

• Why does a token become invalid when pagination is used in a search index-based query?

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.