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It looks like you are asking what order rows will show up on retrieval when two rows with a timestamp cluster key are written to a table. If that is the case then the answer is the rows being returned will be in timestamp order. On the other hand, if you are asking which of two rows with identical keys are going to end up in the table?


Most of the time the timestamp used is supplied by the Cassandra coordinator node receiving the request but the application can supply its own. And how expensive?

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Cassandra is designed from the top down to avoid doing updates. There are no atomic or lock operations in Cassandra. If you were to try to do a simple update in Cassandra without counters or lightweight transactions you would read a column value and then write back the updated version. Because there are no locks or atomic operations there would be no guarantee it would work correctly.

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But it would be fairly fast. With PAXOS which is used in both Lightweight transactions which are not transactions at all Cassandra has to do several round trips to all available nodes containing replicates to complete the operation. Its best to think of an LWT or Counter operation being about 6 times as expensive as the basic update I mentioned above. It is okay to use counters or LWT operations when they are a relatively small part of your workload. It is also important to read about how both work in detail before using them to avoid getting surprised.

This link does a decent job of explaining how lightweight transactions work in Cassandra.

Counters are essentially a special case of LWT. Thanks for writing it! Say you want to store a lot of events, but you also want to filter by special type, and date, and the search by multiple columns, and also order by multiple columns.. Your email address will not be published. Other brands, product and company names on this website may be trademarks or registered trademarks of Pythian or of third parties. Use of trademarks without permission is strictly prohibited.

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Export all data from cassandra

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Tags: Cassandra , Data model , Distributed datbase , Partition key.

Cassandra Use Cases: When To Use and When Not To Use Cassandra

Introduction I have a database server that has these features: High available by design. Can be globally distributed. Allows applications to write to any node anywhere, anytime. Linearly scalable by simply adding more nodes to the cluster. Automatic workload and data balancing. A query language that looks a lot like SQL.

Managed Dependencies (55)

I like, and often promote Cassandra to my customers—for the right use cases. Where Cassandra users go wrong Cassandra projects tend to fail as a result of one or more of these reasons: The wrong Cassandra features were used. The use case was totally wrong for Cassandra. The data modeling was not done properly.

Apache Cassandra and ALLOW FILTERING

Features leading one to believe you can do some of the things everyone expects a relational database to do: Secondary indexes: They have their uses but not as an alternative access path into a table. Counters: They work most of the time, but they are very expensive and should not be used very often. Light weight transactions: They are not transactions nor are they light weight. Batches: Sending a bunch of operations to the server at one time is usually good, saves network time, right? Well in the case of Cassandra not so much.

Materialized views: I got taken in on this one.