Exists query
Exists query is also called NULL query or NULL-value query. This query is used in sparse data to determine whether a column of a row exists. For example, you can query the rows in which the value of the address column is not empty.
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If you want to perform an exists query on a Nested column, you can use nested query.
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If you want to check whether a column contains empty values, you must use ExistsQuery together with mustNotQueries of BoolQuery.
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If one of the following conditions is met, the system considers that a column does not to exist. In this example, the city column is used.
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The type of the city column in the search index is a basic type such as keyword. If a row in which the city column does not exist in the data table, the search index considers that the city column does not exist.
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The type of the city column in the search index is a basic type such as keyword. If a row in which the value of the city column is an empty array in the data table ("city" = "[]"), the search index considers that the city column does not exist.
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Prerequisites
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An OTSClient instance is initialized. For more information, see Initialize an OTSClient instance.
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A data table is created and data is written to the data table. For more information, see Create data tables 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 |
|
fieldName |
The name of the field to query. |
|
query |
The query type. Set this parameter to |
|
getTotalCount |
Whether to return the total number of rows that match the query conditions. Default value: false. Setting this to true reduces query performance. |
|
tableName |
The name of the data table. |
|
indexName |
The name of the search index. |
|
columnsToGet |
The columns to return for each matching row.
|
Examples
The following example queries rows where the pic_des column is not empty.
client.search({
tableName: TABLE_NAME,
indexName: INDEX_NAME,
searchQuery: {
offset: 0,
limit: 10, // Set limit to 0 to return only the row count without data.
query: {
queryType: TableStore.QueryType.EXISTS_QUERY,
query: {
fieldName: "pic_des"
},
},
getTotalCount: true // Set to true to return the total number of matching rows. Default value: false.
},
columnToGet: { // RETURN_SPECIFIED: specified columns; RETURN_ALL: all columns; RETURN_ALL_FROM_INDEX: all columns in the search index; RETURN_NONE: primary key columns only.
returnType: TableStore.ColumnReturnType.RETURN_SPECIFIED,
returnNames: ["Col_1", "Col_2", "Col_3"]
}
}, 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.