Given you only have 16 columns vs. over 200 ... I would expect a substantial improvement in writes, but not 5x. Ditto reads. I would be interested to understand where that 5x comes from.
*.......* *Daemeon C.M. ReiydelleUSA (+1) 415.501.0198London (+44) (0) 20 8144 9872* On Thu, Feb 18, 2016 at 8:20 PM, Chandra Sekar KR < chandraseka...@hotmail.com> wrote: > Hi, > > > I'm looking for help in arriving at pros & cons of using MAP, UDT & JSON > (Text) data types in Cassandra & its ease of use/impact across other DSE > products - Spark & Solr. We are migrating an OLTP database from RDBMS to > Cassandra which has 200+ columns and with an average daily volume of 25 > million records/day. The access pattern is quite simple and in OLTP the > access is always based on primary key. For OLAP, there are other access > patterns with a combination of columns where we are planning to use Spark & > Solr for search & analytical capabilities (in a separate DC). > > > The average size of each record is ~2KB and the application workload is of > type INSERT only (no updates/deletes). We conducted performance tests on > two types of data models > > 1) A table with 200+ columns similar to RDBMS > > 2) A table with 15 columns where only critical business fields are > maintained as key/value pairs and the remaining are stored in a single > column of type TEXT as JSON object. > > > In the results, we noticed significant advantage in the JSON model where > the performance was 5X times better than columnar data model. > Alternatively, we are in the process of evaluating performance for other > data types - MAP & UDT instead of using TEXT for storing JSON object. > Sample data model structure for columnar, json, map & udt types are given > below: > > > > > I would like to know the performance, transformation, compatibility & > portability impacts & east-of-use of each of these data types from Search & > Analytics perspective (Spark & Solr). I'm aware that we will have to use > field transformers in Solr to use index on JSON fields, not sure about MAP > & UDT. Any help on comparison of these data types in Spark & Solr is highly > appreciated. > > > Regards, KR >
