Creating a materialized view

Create materialized views with the CREATE MATERIALIZED VIEW command.Materialized views are suited for high cardinality data. The data in a materialized view is arranged serially based on the view's primary key. Materialized views cause hotspots when low cardinality data is inserted.Secondary indexes are suited for low cardinality data. Queries of high cardinality columns on secondary indexes require Cassandra to access all nodes in a cluster, causing high read latency. Restrictions for materialized views:Include all of the source table's primary keys in the materialized view's primary key. Only one new column can be added to the materialized view's primary key. Static columns are not allowed. Exclude rows with null values in the materialized view primary key column. You can create a materialized view with its own WHERE conditions and its own properties.Materialized view exampleThe following table is the original, or source, table for the materialized view examples in this section.CREATE TABLE cyclist_mv (cid UUID PRIMARY KEY, name text, age int, birthday date, country text);This table holds values for the name, age, birthday, and country affiliation of several cyclists.Thecyclist_mvtable can be the basis of a materialized view that uses age in the primary key.CREATE MATERIALIZED VIEW cyclist_by_age AS SELECT age, birthday, name, country FROM cyclist_mv WHERE age IS NOT NULL AND cid IS NOT NULL PRIMARY KEY (age, cid);ThisCREATE MATERIALIZED VIEWstatement has several features:The AS SELECT phrase identifies the columns copied from the base table to the materialized view. The FROM phrase identifies the source table from which Cassandra will copy the data. The WHERE clause must include all primary key columns with the IS NOT NULL phrase so that only rows with data for all the primary key columns are copied to the materialized view. As with any table, the materialized view must specify the primary key columns. Because cyclist_mv, the source table, uses cid as its primary key, cid must be present in the materialized view's primary key.Note: In this materialized view, age is used as the primary key and cid is a clustering column. In Cassandra3.0 and earlier, clustering columns have a maximum size of 64 KB. Because the new materialized view is partitioned by age, it supports queries based on the cyclists' ages.SELECT age, name, birthday FROM cyclist_by_age WHERE age = 18;Other materialized views, based on the same source table, can organize information by cyclists' birthdays or countries of origin.CREATE MATERIALIZED VIEW cyclist_by_birthday AS SELECT age, birthday, name, country FROM cyclist_mv WHERE birthday IS NOT NULL AND cid IS NOT NULLPRIMARY KEY (birthday, cid);CREATE MATERIALIZED VIEW cyclist_by_country AS SELECT age, birthday, name, country FROM cyclist_mv WHERE country IS NOT NULL AND cid IS NOT NULLPRIMARY KEY (country, cid);The following queries use the new materialized views.SELECT age, name, birthday FROM cyclist_by_country WHERE country = 'Netherlands';SELECT age, name, birthday FROM cyclist_by_birthday WHERE birthday = '1987-09-04';When another INSERT is executed on cyclist_mv, Cassandra updates the source table and both of these materialized views. When data is deleted from cyclist_mv, Cassandra deletes the same data from any related materialized views.Cassandra can only write data directly to source tables, not to materialized views. Cassandra updates a materialized view asynchronously after inserting data into the source table, so the update of materialized view is delayed. Cassandra performs a read repair to a materialized view only after updating the source table.