cassandra | Mirror of Apache Cassandra

No, it’s not possible to do only with CQL - you need to have some code or tool to do that - it should scan the whole database, read the data and put them into destination column. Besides trying to write your own code, that it’s usually hard to write correctly you can use:

• DSBulk - you can unload data into CSV or JSON file, convert the data into specific representation by using sed or something like, and load data into the new column. But transformation step is something that you will need to implement, and it could be hard to debug if you have data with quotes, etc.
• Spark + Spark Cassandra Connector (even in the local mode) - although it's still a piece of code, it would be easier to implement from my point of view. Just start pyspark with options specified in the documentation, read data from Cassandra, transform, and store them back into Cassandra. Something like this (not tested):

I answered this question a while ago, which is similar: Replication Factor to use for system_auth

Due to issues that can happen with larger clusters which fluctuate in size, we now treat system_auth like we do any other keyspace. That is, we set system_auth's RF to 3 in each DC.

tl;dr;, if you're using NetworkTopologyStrategy on your non-system keyspaces, then you should also be using it for system_auth. Same with your RF; I'd always match the RF of system_auth with that of my "normal" keyspaces, as well.

No, the replication strategy and RF used on system_auth does not typically cause query latency. That is of course, unless any of the Security cache settings have been altered. 10 years of working with Cassandra, I've never had to change those: https://docs.datastax.com/en/security/5.1/security/secAuthCacheSettings.html

queries wasting time on (tracing): "Executing single-partition query on roles [ReadStage-X]"

This statement got me thinking: Are you tracing queries in cqlsh while logged in as the default cassandra user? That user does trigger some cqlsh operations to execute at QUORUM. Could also be that maybe the query consistency and connection consistency are set differently. Just a thought.

You're right in that performance is both:

• subjective
• depends largely on data size

I can tell you that I have done this exercise as well. To that end, I think it's important to share this comparison from DB-Engines.com.

In terms of performance, the biggest thing I'd be looking at is how each handles consistency. As a general rule, databases which enforce stronger levels of consistency typically have to sacrifice performance.

• BigTable == strong-consistent
• Cassandra == eventually consistent

Other factors worth considering, are the fact that BigTable limits you to Google Cloud (GCP). And if you don't want to lose performance over the network, you'll also need to pay for more (Janus) instances on GCP for data locality.

In terms of raw DB-Engine "score," Cassandra is currently at 114.112, while BigTable is at a paltry 3.582. These scores will change month-to-month, but in general this signifies that Cassandra has a much stronger community around it. Similarly, Cassandra has 18182 questions on this site, while BigTable only has 449. Bottom line, is that it'll be much easier to get support and answers to questions.

Just based on the underlying strength of the community, Cassandra is the better option here.

Having supported JanusGraph on Cassandra for the last few years, I can tell you that overall it's been solid. The difficulties tend to come into play with bulk data loading. But outside of that, things seem to run pretty well.

The DriverTimeoutException gets thrown when the driver doesn't get a reply from the coordinator node. It uses the basic request timeout default of 2 seconds:

The problem is the connection with the cassandra. Make sure that you've been created the keyspace-name on cassandra. After that in your project declare a Bean Configuration with the keyspace, in my case mykeyspace. You can visit https://kayaerol84.medium.com/cassandra-cluster-management-with-docker-compose-40265d9de076 for more details about setting up the keyspace.

You can update the ttl to desired value while updating the column. I mean you can achieve it programatically. Please go through this page ( https://docs.datastax.com/en/cql-oss/3.3/cql/cql_using/useExpireExample.html ) for examples.

Cassandra doesn't have joins, so you can't do it - if you need to perform the join, then it should be done in your application.

Cassandra encourages the data denormalization, when you can copy necessary data into another table to avoid joining when reading data - like, for cart table, you can copy price/description from the product table, and then when displaying the cart you won't need to query the product table.

I recommend to read first chapters of "Casasndra: The Definitive Guide, 3rd edition" book - it's freely available. This will help you with understanding how to model data for Cassandra

I work with hundreds of companies who use Cassandra on a daily basis and most of these companies do things on internet scale.

Most of their SLAs require ~6 millisecond read latency 95% of the time at peak app traffic. For that reason, a 2-second latency is a read timeout in Cassandra terms.

For those who say it is slow, I'll let the tech giants do the talking for Cassandra -- Apple, Netflix, Uber, Visa, FedEx, Sony, GE, Expedia and the list goes on and on and on. :)

You want to use the authorized_key module.

For example: