Perform match phrase queries by using Tablestore SDK for Python - Tablestore

A match phrase query is similar to match query, except that a match phrase query evaluates the positions of tokens. A row meets the query condition only when the order and positions of the tokens in the row match the order and positions of the tokens that are contained in the keyword. If the tokenization method for the column that you want to query is fuzzy tokenization, a match phrase query is performed at a lower latency than a wildcard query.

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. You can perform match queries on TEXT columns.
text	The keyword that is used to match the value of the column when you perform a match phrase query. If the column that you want to query is a TEXT column, the keyword is tokenized into multiple tokens based on the analyzer type that you specify when you create the search index. By default, single-word tokenization is performed if you do not specify the analyzer type when you create the search index. For example, if you perform a match phrase query by using the phrase "this is", "..., this is tablestore" and "this is a table" are returned. "this table is ..." or "is this a table" is not returned.
query	The query type. Set this parameter to MatchPhraseQuery.
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 the limit 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. If you set the return_type field to ColumnReturnType.SPECIFIED, you can use the column_names field to specify the columns that you want to return. If you set the return_type field to ColumnReturnType.ALL, all columns are returned. If you set the return_type field to ColumnReturnType.NONE, only the primary key columns are returned.

Examples

The following examples describe how to use match phrase query to query the rows whose Col_Text column values match the 'this is' phrase in sequence.

Perform match phrase query by using Tablestore SDK for Python V5.2.1 or later

If you use Tablestore SDK for Python V5.2.1 or later to perform a match phrase query, a SearchResponse object is returned by default. The following code provides a sample request:

query = MatchPhraseQuery('Col_Text', 'this is')
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 = MatchPhraseQuery('Col_Text', 'this is')
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 match phrase 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 match phrase query, results of the TUPLE type are returned by default. The following sample code provides a sample request:
```
query = MatchPhraseQuery('Col_Text', 'this is')
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.