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From Anuj Wadehra <>
Subject Migrating to CQL and Non Compact Storage
Date Sun, 10 Apr 2016 18:09:25 GMT
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:
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?


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