Hello Somnath, Kylin 2.5 needs Spark 2.1 (not Spark 2.2); The guide for Kylin 2.5 is in https://kylin.apache.org/docs/tutorial/cube_spark.html; (the link you provided above is the tutorial for Kylin 2.0, not matched with your version); Please try this: 1) build the assembly jar from the spark 2.1 that shipped with Kylin; 2) copy the sample cube to a new one, edit it, and then change the "engine type" to "spark"; Just take a try, it should be minor issue as many users are using Spark now. ... View more

What's the version of Kylin and HDP that you're running? Please provide the full error trace for analysis. Also, please set SPARK_HOME to KYLIN_HOME/spark before starting up Kylin. Building Cube ... View more

(sorry for splitting my comments into several posts, as this forum doesn't allow comment more than 600 characters... ) Welcome to join our dev mailing list dev@kylin.apache.org (send to dev-subscribe@kylin.apache.org to subscribe), there are a lot of discussions; Regards, shaofengshi@apache.org ... View more

6. "The more segments the slower performance can get (more scans)" comment: Yes, usually we suggest user to control the segment number e.g no more than 10, to gain a better query performance; But if the partition date column appears in the filtering condition, Kylin can smartly skip those unrelated segments, for this case, the segment number doesn't matter. ... View more

5. “MDX adoption is very low, therefore its not currently supported” comment: If anyone want to do MDX using Kylin, we suggest try Mondrian, some users has been able to run that successfully, here is a document: https://www.inovex.de/fileadmin/files/Vortraege/2015/big-data-mdx-with-mondrian-and-apache-kylin-sebastien-jelsch-pcm-11-2015.pdf ... View more

3. "Simple measures only (counts, max, min and sum). No custom calcs, ratios, etc." comment: the custom measure support is on the way, and will be released soon: https://issues.apache.org/jira/browse/KYLIN-976 4. "16 dimensions seem like an upper limit, but that's not confirmed." comment: the real upper limit is 64, but usually we suggest user to control the cube expansion rate by picking no more than 20 dimensions; ... View more

2. "MR overhead with building cubes (“query yesterdays data”). Lots of shuffling. Does aggregations on the reduce side" comment: you're right, as-is cube algorithm may cause a lot of shuffling among the hadoop nodes; We have realized this and introduced a new algorithm called "fast-cubing", which will do mapper side aggregation, aming to reduce the network IO and reduce the MR time; it will be released in Kylin v2.0. ... View more

Hello ccasano, This is Shaofeng from Apache Kylin community; Thanks for the trial and compose such a good summary on Kylin, we think it is very helpful for end users; Here I want to add some comments regarding some of your questions: 1. "base level data resides in Hive and not the cube. The cube contains only aggregate data." comment: you're correct; so far Kylin doesn't save the raw data; but it has been under development; In a future release, user will be able to query both aggregated data as well as raw data from Kylin: https://issues.apache.org/jira/browse/KYLIN-1122 ... View more