In this article we will discuss overview of Materialized views and its importance. In Cassandra Materialized views play an important role such that Materialized views are suited for high cardinality data. We also discuss How we can create, Alter and Drop Materialized views. let’s discuss one by one.
Materialized view is work like a base table and it is defined as CQL query which can queried like a base table. Materialized view is very important for de-normalization of data in Cassandra Query Language is also good for high cardinality and high performance. Let’s understand with an example.
Now, first we are going to define the base table (base table – User_information) and User1 is the keyspace name. User_name is the partitioning key by which we will get the result in sorted way. same primary key will be used for materialized view and another one more column can be add in materialized view for primary key to get the user information because of restriction to define primary key in materialized view. User_name, User_email, User_password and User_address are the column’s of base table. let’s have a look.
To create table for user information used the following CQL query.
CREATE TABLE User1.User_information ( User_name text PRIAMRY KEY, User_email text, User_password text, User_address text );
Now, let us consider that If we want to find the user information with the help of user email then we need to create a new table and by defining email as partition key we can get the user information but we have another better option which is called materialized view.
so, now let’s create Materialized of the above given table which is also called the base table. To create materialized view used the following CQL query.
Syntax: Creating Materialized view:
CREATE MATERIALIZED VIEW [IF NOT EXISTS] [keyspace_name.] view_name AS SELECT column_list FROM [keyspace_name.] base_table_name WHERE column_name IS NOT NULL [AND column_name IS NOT NULL ...] [AND relation...] PRIMARY KEY ( column_list ) [WITH [table_properties] [AND CLUSTERING ORDER BY (cluster_column_name order_option )]]
CREATE MATERIALIZED VIEW User1.Users_by_User_email AS SELECT User_email, User_password, User_address FROM User_information WHERE User_name IS NOT NULL AND User_email IS NOT NULL PRIMARY KEY (User_email, User_name );
To perform operation such that read data from materialized view used the following CQL query.
SELECT * FROM Users_by_User_email WHERE User_email = ? ;
In materialized view there are following restriction that must follow.
- In materialized view whatever the primary column in base table must contain in materialized view table that ensure every row of MV (materialized view) is correspond to the base table.
- In materialized view only we can add one more column that is not a primary column in base table.
Let’s take an example to understand the concept.
CREATE TABLE base_table ( Key1 int, Col1 int, Col2 int, Col3 int, Col4 text, PRIAMRY KEY (key1, Col1, Col2) );
Materialized view of above given base table is allowed. Let’s have a look.
Case-1: CREATE MATERIALIZED VIEW test_MV1 AS SELECT * FROM test_MV1 WHERE key1 IS NOT NULL AND Col1 IS NOT NULL AND Col2 IS NOT NULL PRIMARY KEY (Col1, key1, Col2); Case-2: CREATE MATERIALIZED VIEW test_MV2 AS SELECT * FROM test_MV2 WHERE key1 IS NOT NULL AND Col1 IS NOT NULL AND Col2 IS NOT NULL AND Col3 IS NOT NULL PRIMARY KEY (Col3, key1, Col1, Col2);
Materialized view of above given base table is NOT allowed. Let’s have a look.
Case-1: CREATE MATERIALIZED VIEW test_MV1 AS SELECT * FROM test_MV2 WHERE key1 IS NOT NULL AND Col1 IS NOT NULL AND Col2 IS NOT NULL AND Col3 IS NOT NULL PRIMARY KEY (Col3, Col4, key1, Col1, Col2); // * ERROR : it will give an error that Col3 and Col4 is not primary key in base table. Case-2: CREATE MATERIALIZED VIEW test_MV1 AS SELECT * FROM test_MV2 WHERE Col1 IS NOT NULL AND Col2 IS NOT NULL PRIMARY KEY (Col1, Col2); // * ERROR : it will give an error that key1 is primary key in base table that must contain in materialized view.
Alter Materialized View:
Given below is the CQL query to alter the basic properties of Materialized view using ALTER command. let’s have a look.
ALTER MATERIALIZED VIEW [keyspace_name.] view_name [WITH table_options]
Drop Materialized View:
We can remove materialized view table by using DROP command and there will be no affect on the base table.
DROP MATERIALIZED VIEW [IF EXISTS] [keyspace_name.] view_name
For example, to DROP Materialized view used the following CQL Query.
DROP MATERIALIZED VIEW User1.Users_by_User_email ;
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- Differences between Views and Materialized Views in SQL
- Materialized views with Practical approach in Cassandra
- Local Indexing and Materialized views in Cassandra 3.0
- SQL | Views
- Static type using batch in Cassandra
- Role of keys in Cassandra
- High Availability Mechanism in Cassandra
- Apache Cassandra tools
- Blob conversion function in Cassandra
- Designing models in Cassandra
- Introduction to Apache Cassandra
- Apache Cassandra (NOSQL database)
- Architecture of Apache Cassandra
- Overview of User Defined Type (UDT) in Cassandra
- Overview of Data modeling in Apache Cassandra
- Concept of indexing in Apache Cassandra
- Collection Data Type in Apache Cassandra
- Pre-defined data type in Apache Cassandra
- Monitoring cluster in Cassandra
- Virtual machine installation for Cassandra CQL query
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