If a cluster is exhibiting poor read performance, there are some obvious things to check on the application and data model (table definition) before adjusting any configuration settings. As previously mentioned, tables in Cassandra must be designed based on the queries that they are required to serve. If application teams are complaining about operation slowness for multi-key queries or queries that contact multiple nodes, there is little that can be done to improve the situation. On the other hand, if you are confident about the table design and are not violating any known anti-patterns (see the Cassandra anti-patterns section, under Other performance considerations), then configuration in some of these areas may be helpful.
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You're reading from Mastering Apache Cassandra 3.x - Third Edition
Aaron Ploetz is the NoSQL Engineering Lead for Target, where his DevOps team supports Cassandra, MongoDB, and Neo4j. He has been named a DataStax MVP for Apache Cassandra three times and has presented at multiple events, including the DataStax Summit and Data Day Texas. Aaron earned a BS in Management/Computer Systems from the University of Wisconsin-Whitewater, and an MS in Software Engineering from Regis University. He and his wife, Coriene, live with their three children in the Twin Cities area.
Read more about Aaron Ploetz
Tejaswi Malepati is the Cassandra Tech Lead for Target. He has been instrumental in designing and building custom Cassandra integrations, including a web-based SQL interface and data validation frameworks between Oracle and Cassandra. Tejaswi earned a master's degree in computer science from the University of New Mexico, and a bachelor's degree in electronics and communication from Jawaharlal Nehru Technological University in India. He is passionate about identifying and analyzing data patterns in datasets using R, Python, Spark, Cassandra, and MySQL.
Read more about Tejaswi Malepati
Nishant Neeraj is an independent software developer with experience in developing and planning out architectures for massively scalable data storage and data processing systems. Over the years, he has helped to design and implement a wide variety of products and systems for companies, ranging from small start-ups to large multinational companies. Currently, he helps drive WealthEngine's core product to the next level by leveraging a variety of big data technologies.
Read more about Nishant Neeraj
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Aaron Ploetz is the NoSQL Engineering Lead for Target, where his DevOps team supports Cassandra, MongoDB, and Neo4j. He has been named a DataStax MVP for Apache Cassandra three times and has presented at multiple events, including the DataStax Summit and Data Day Texas. Aaron earned a BS in Management/Computer Systems from the University of Wisconsin-Whitewater, and an MS in Software Engineering from Regis University. He and his wife, Coriene, live with their three children in the Twin Cities area.
Read more about Aaron Ploetz
Tejaswi Malepati is the Cassandra Tech Lead for Target. He has been instrumental in designing and building custom Cassandra integrations, including a web-based SQL interface and data validation frameworks between Oracle and Cassandra. Tejaswi earned a master's degree in computer science from the University of New Mexico, and a bachelor's degree in electronics and communication from Jawaharlal Nehru Technological University in India. He is passionate about identifying and analyzing data patterns in datasets using R, Python, Spark, Cassandra, and MySQL.
Read more about Tejaswi Malepati
Nishant Neeraj is an independent software developer with experience in developing and planning out architectures for massively scalable data storage and data processing systems. Over the years, he has helped to design and implement a wide variety of products and systems for companies, ranging from small start-ups to large multinational companies. Currently, he helps drive WealthEngine's core product to the next level by leveraging a variety of big data technologies.
Read more about Nishant Neeraj