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Scaling Cassandra can be daunting the first time around. DataStax has a great introduction to Cassandra deletions that I would definitely recommend reading. Well, actually… DeletionsĮxecuting a DELETE in CQL does not actually delete data.
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Twenty-four hours after that query is executed, the data will be deleted. * Expiring Data in 24 Hours */ INSERT INTO myTable (id, myField) VALUES (2, 9) USING TTL 86400 This is accomplished with the USING TTL command (values are in seconds). Meaning that you can set a row to expire 24 hours from the time it gets created. Time to LiveĬQL enables you to set a TTL on a row. This means that both inserts and updates are extremely fast. Without a read, there is no way to know if the data being inserted is replacing an existing record. Because again, CQL does not perform a read while inserting. Similarly as unintuitive, an INSERT statement will actually replace data if it exists. However, if the row does not exist, it will still get created.
APACHE CASSANDRA SQL PROMPT UPDATE
* Updating data */ UPDATE myTable SET myField = 2 WHERE id = 6 This is because, unlike in SQL, a read is not performed during the update. The concept of cheap writes extends to updating data. You’re not just going to have to de-normalize, you’re going to have to forget about normalization all together. Having a column family to represent every query makes reads much more efficient. You can still store them separately, but you should also store them together. You want to look up addresses that correspond to a person? Then make a column family that consists of people and addresses. In other words, any query you plan to do in the future should already be organized into a column family.
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Write everything the way you want to read it. And if you take only one thing away from this post, let it be this: The problem is that reads in Cassandra tend to be more expensive than you might be used to when dealing with a relational database. So without the relational tools of SQL, we need another strategy to represent these relationships. Leaving these features out is important because it makes writing and retrieving data from Cassandra much more efficient.īut sets of data tend to have relationships with one another. There is no support for things like JOIN, GROUP BY, or FOREIGN KEY. None of the standard relational stuff is going to work in CQL. In a production environment, likely spread across several data-centers, a keyspace would be created with a different strategy and replication factor. Note that the example above is the simplest form. This difference necessitates a different syntax for creating and manipulating data: Creating databases: /* Create a new keyspace in CQL */ CREATE KEYSPACE myDatabase WITH replication = /* Create a new database in SQL */ CREATE DATABASE myDatabase Ĭassandra’s keyspaces require more specifications than a standard relational database. Simplistically, a Cassandra keyspace is a SQL database, and a Cassandra column family is a SQL table (CQL allows you to interchange the words “TABLE” and “COLUMNFAMILY” for convenience). DifferencesĬassandra is a non-relational database, and so uses different concepts to store and retrieve data. But there are quite a few differences once you get beyond the basics. The following is both valid CQL and SQL: Valid CQL and SQL USE myDatabase /* Creating Tables */ CREATE TABLE IF NOT EXISTS myTable (id INT PRIMARY KEY) /* Altering Tables /* ALTER TABLE myTable ADD myField INT /* Creating Indexes */ CREATE INDEX myIndex ON myTable (myField) /* Inserting Data */ INSERT INTO myTable (id, myField) VALUES (1, 7) /* Selecting Data */ SELECT * FROM myTable WHERE myField = 7 /* Counting Data */ SELECT COUNT(*) FROM myTable /* Deleting Data */ DELETE FROM myTable WHERE myField = 7 įrom this, its easy to think that the two languages work just the same. In fact, a lot of basic things are even exactly the same. Many queries are very similar between the two. This similarity lowers the barrier of entry for users familiar with relational databases. CQL is purposefully similar to Structured Query Language (SQL) used in relational databases like MySQL and Postgres. The Cassandra Query Language (C QL) was created to provide the necessary abstraction.
APACHE CASSANDRA SQL PROMPT DRIVERS
Exposing this low level interface also meant that language-specific drivers often needed to make significant updates from version to version.
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This introduced an additional hurdle for new users coming from a relational database background. Manipulating data this way was cumbersome and required learning the details of the API. When Apache Cassandra was originally released, it featured a command line interface for dealing with thrift.