Hi We are on 2.0.14 and Thrift. We are planning to migrate to CQL soon but facing some challenges. We have a cf with a mix of statically defined columns and dynamic columns (created at run time). For reading dynamic columns in CQL, we have two options: 1. Drop all columns and make the table schema less. This way, we will get a Cql row for each column defined for a row key--As mentioned here: http://www.datastax.com/dev/blog/thrift-to-cql3 2.Migrate entire data to a new non compact storage table and create collections for dynamic columns in new table. In our case, we have observed that approach 2 causes 3 times slower performance in Range scan queries used by Spark. This is not acceptable. Cassandra 3 has optimized storage engine but we are not comfortable moving to 3.x in production. Moreover, data migration to new table using Spark takes hours.
Any suggestions for the two issues? ThanksAnuj Sent from Yahoo Mail on Android
