Create a secondary index by using Tablestore SDK for Python - Tablestore

The secondary index feature allows you to query data based on the primary key of a data table and the index columns of the secondary index that is created for the data table. If you want to use the attribute columns of a data table to query data, you can create a secondary index for the data table to accelerate data queries. When you create a secondary index for a data table, you can set the index columns or attribute columns of the secondary index to the predefined columns that you specified when you created the data table. After you create a secondary index, you can use the secondary index to query data.

Note

Secondary indexes are classified into global secondary indexes and local secondary indexes. For more information about the secondary index feature, see Overview.
You can create one or more index tables when you create a data table by calling the CreateTable operation. For more information, see Create a data table.

Prerequisites

An OTSClient instance is initialized. For more information, see Initialize an OTSClient instance.
A data table for which the max_version parameter is set to 1 is created. One of the following conditions must be met by the time_to_live parameter of the data table: For more information, see Create a data table.
- The time_to_live parameter of the data table is set to -1, which specifies that the data in the data table never expires.
- The time_to_live parameter of the data table is set to a value other than -1, and update operations on the data table are prohibited.
Predefined columns are specified for the data table.

Usage notes

The name of an index table must be different from the name of an existing time series table or data table.
When you create a secondary index, Tablestore automatically adds the primary key columns of the data table that are not specified as index columns to the secondary index as the primary key columns of the secondary index.
When you create a local secondary index, the first primary key column of the index table must be the same as the first primary key column of the data table.

Parameters

Parameter	Description
main_table_name	The name of the data table.
index_meta	The schema information about the index table. The schema information contains the following items: index_name: the name of the index table. primary_key_names: the primary key of the index table. The primary key is a combination of all primary key columns and a random number of predefined columns of the data table. If you want to create a local secondary index, the first primary key column of the index table must be the same as the first primary key column of the data table. defined_column_names: the attribute columns of the index table. The attribute columns are a combination of predefined columns of the data table. index_type: the type of the index table. Valid values: IT_GLOBAL_INDEX and IT_LOCAL_INDEX. If you do not specify the index_type parameter or you set the index_type parameter to IT_GLOBAL_INDEX, a global secondary index is created. Tablestore automatically synchronizes data from the indexed columns and primary key columns of the data table to the columns of the index table that you want to create in asynchronous mode. The synchronization latency is within a few milliseconds. If you set the index_type parameter to IT_LOCAL_INDEX, a local secondary index is created. Tablestore automatically synchronizes data from the indexed columns and primary key columns of the data table to the columns of the index table that you want to create in synchronous mode. After data is written to the data table, you can immediately query the data in the index table.
include_base_data	Specifies whether to include the existing data of the data table in the index table. If you set the include_base_data parameter to true, the index table includes the existing data. If you set the include_base_data parameter to false, the index table excludes the existing data.

Examples

Create a global secondary index

The following sample code provides an example on how to create a secondary index for a data table. In the example, the primary key columns of the data table are pk1 and pk2. The primary key columns that are specified for the secondary index are definedcol1 and pk1. The attribute columns that are specified for the secondary index are definedcol2 and definedcol3.

# Specify the metadata of the index table. 
# Specify the name, primary key columns, and attribute columns of the index table in sequence. 
index_meta = SecondaryIndexMeta('<INDEX_NAME>', ['definedcol1', 'pk1'], ['definedcol2', 'definedcol3'])
# Specify the name of the data table and specify that the index table does not include the existing data of the data table. 
client.create_secondary_index('<TABLE_NAME>', index_meta, False)
# Specify the name of the data table and specify that the index table includes the existing data of the data table. 
# After you create the index table, the existing data of the data table is synchronized to the index table. After the existing data is synchronized, you can use the index table to query all data in the data table. The time that is required for synchronization varies based on the amount of data to synchronize. 
# client.create_secondary_index('<TABLE_NAME>', index_meta, True)

Create a local secondary index

# Specify the metadata of the index table. 
# Specify the name, primary key columns, attribute columns, and type of the index table in sequence. 
# The first primary key column of a local secondary index must be the same as the first primary key column of the data table. 
index_meta = SecondaryIndexMeta('<INDEX_NAME>', ['pk1', 'definedcol1'], ['definedcol2', 'definedcol3'],index_type= SecondaryIndexType.LOCAL_INDEX)
# Specify the name of the data table and specify that the index table does not include the existing data of the data table.
client.create_secondary_index('<TABLE_NAME>', index_meta, False)
# Specify the name of the data table and specify that the index table includes the existing data of the data table. 
# After you create the index table, the existing data of the data table is synchronized to the index table. After the existing data is synchronized, you can use the index table to query all data in the data table. The time that is required for synchronization varies based on the amount of data to synchronize. 
# client.create_secondary_index('<TABLE_NAME>', index_meta, True)

References

After you create a secondary index, you can use the secondary index to read a single row of data or data whose primary key value is within a specific range. For more information, see Use a secondary index to read data.
You can delete a secondary index that you no longer use. For more information, see Delete a secondary index.