You can use match query to query data in a table based on approximate matches. Tablestore tokenizes the values in the TEXT field and the keyword you use to perform a match query based on the analyzer type that you specify. This way, Tablestore can perform a match query based on the tokens. We recommend that you use match phrase query for TEXT fields for which fuzzy tokenization is used to ensure high performance in fuzzy queries.
Prerequisites
An OTSClient 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 data tables and Write data.
A search index is created for the data table. For more information, see Create a search index.
Parameters
Parameter | Description |
tableName | The name of the data table. |
indexName | The name of the search index. |
offset | The position from which the current query starts. |
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 specific data, set the limit parameter to 0. |
queryType | The type of the query. To use match query, set this parameter to TableStore.QueryType.MATCH_QUERY. |
fieldName | The name of the field that you want to match. Match query applies to TEXT fields. |
text | The keyword that is used to match the value of the field when you perform a match query. If the field that you want to match is a TEXT field, the keyword is tokenized into multiple tokens based on the analyzer type that you specify when you create the search index. If you do not specify the analyzer type when you create the search index, single-word tokenization is performed. For example, if the field that you want to match is a TEXT field, you set the analyzer type to single-word tokenization, and you use "this is" as a search keyword, you can obtain query results such as "..., this is tablestore", "is this tablestore", "tablestore is cool", "this", and "is". |
operator | The logical operator. By default, OR is used as the logical operator, which specifies that a row meets the query conditions when the field value contains at least the minimum number of matched tokens. If you set the operator parameter to AND, the row meets the query conditions only if the field value contains all matched tokens. |
minimumShouldMatch | The minimum number of matched tokens contained in the value of the field. A row is returned only if the value of the field specified by the fieldName parameter in the row contains at least the minimum number of matched tokens. Note You must use the minimumShouldMatch parameter together with the OR logical operator. |
getTotalCount | Specifies whether to return the total number of rows that meet the query conditions. Default value: false. If you set this parameter to true, the query performance is compromised. |
columnToGet | Specifies whether to return all columns of each row that meets the query conditions. You can configure returnType and returnNames for this parameter.
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Examples
The following sample code provides an example on how to query the rows in which the value of the Col_Keyword column matches "hangzhou" in a table:
/**
* Query the rows in which the value of the Col_Keyword column matches "hangzhou" in a table. Tablestore returns the total number of rows that meet the query conditions and the specific data of some of these rows.
*/
client.search({
tableName: TABLE_NAME,
indexName: INDEX_NAME,
searchQuery: {
offset: 0,
limit: 10, // To query only the number of rows that meet the query conditions without specific data, set the limit parameter to 0.
query: { // Set the query type to MatchQuery.
queryType: TableStore.QueryType.MATCH_QUERY,
query: {
fieldName: "Col_Keyword", // Specify the name of the field that you want to match.
text: "hangzhou" // Specify the keyword that is used to match the value of the field.
}
},
getTotalCount: true // Specify whether to return the total number of rows that meet the query conditions. Default value: false.
},
columnToGet: { // Specify the columns that you want to return. You can set the parameter to RETURN_SPECIFIED to return the specified columns, RETURN_ALL to return all columns, RETURN_ALL_FROM_INDEX to return all columns in the search index, or RETURN_NONE to return only the primary key columns.
returnType: TableStore.ColumnReturnType.RETURN_ALL
}
}, function (err, data) {
if (err) {
console.log('error:', err);
return;
}
console.log('success:', JSON.stringify(data, null, 2));
});FAQ
References
The following query types are supported by search indexes: term query, terms query, match all query, match query, match phrase query, prefix query, range query, wildcard query, Boolean query, geo query, nested query, vector query, and exists query. You can select a query type to query data based on your business requirements.
If you want to sort or paginate the rows that meet the query conditions, you can use the sorting and paging feature. For more information, see Sorting and paging.
If you want to collapse the result set based on a specific column, you can use the collapse (distinct) feature. 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, such as obtaining the extreme values, sum, and total number of rows, you can perform aggregation operations or execute SQL statements. For more information, see Aggregation and SQL query.
If you want to quickly 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.