Hello Jack What do you mind with "the map datatype with string key values effectively gives you extensible columns"
Regards On Tue, Mar 1, 2016 at 1:34 PM, Jack Krupansky <jack.krupan...@gmail.com> wrote: > OLAP using Cassandra and Spark: > > http://www.slideshare.net/EvanChan2/breakthrough-olap-performance-with-cassandra-and-spark > > What is the cardinality of your cube dimenstions? Obviously any > multi-dimensional data must be flattened. > > Cassandra tables have fixed named columns, but... the map datatype with > string key values effectively gives you extensible columns. > > > > -- Jack Krupansky > > On Tue, Mar 1, 2016 at 11:22 AM, Andrés Ivaldi <iaiva...@gmail.com> wrote: > >> Jonathan thanks for the link, >> I believe that maybe is good as Data Store part, because is fast for I/o >> and handles Time Series, for analytics could be with Apache Ignite and/or >> Apache Spark >> what it worries me is that looks very complex create the structure for >> each Fact table and then extend >> >> regards. >> >> On Sun, Feb 28, 2016 at 12:28 PM, Jonathan Haddad <j...@jonhaddad.com> >> wrote: >> >>> Cassandra is primarily used as an OLTP database, not analytics. You >>> should watch this 30 min video discussing Cassandra core concepts (coming >>> from a relational background): >>> https://academy.datastax.com/courses/ds101-introduction-cassandra >>> >>> On Sun, Feb 28, 2016 at 5:40 AM Andrés Ivaldi <iaiva...@gmail.com> >>> wrote: >>> >>>> Hello, At my work we are looking for new technologies for an Analysis >>>> Engine, and we are evaluating differents technologies one of them is >>>> Cassandra as our Data repository. >>>> >>>> Now we can execute query analysis agains an OLAP Cube and RDBMS, using >>>> MSSQL as our data repository. Cube is obsolete and SQL server engine is >>>> slow as data repository. >>>> >>>> I don't know much about cassandra, I read some books, and looks to fit >>>> well on what we are needing, but there are some things that looks like a >>>> problem for us. >>>> >>>> Our engine is designed to be scalable, flexible and dynamic, any user >>>> can add new dimensions or measures from any source, all the data is stored >>>> on Cube(this is fixed data) and MSSQL(dynamic data) so we have decoupled >>>> tables with the dimension values. >>>> >>>> >>>> Ok, with the context given I'll like to clear some doubts >>>> >>>> - I able to flat the table with all the possible dimension values to >>>> cassandra, creating the pk against the dimension columns? this will give me >>>> the "sensation" of data pivot over the PK columns? If correct, what if I >>>> want to select the order of the columns, or add another or reduce them? >>>> - It's possible to extend the values of a row dynamically? What we do >>>> often is join row against a value of a mapped external data value to extend >>>> the dimensions hierarchical value structure (ie state->Country->Continent) >>>> >>>> I know we can do some of this things in the core of our engine, like >>>> the dimension extension of the values or reduce columns, but as we are >>>> evaluating differents technologies is good to know. >>>> >>>> Regards!! >>>> >>>> >>>> -- >>>> Ing. Ivaldi Andres >>>> >>> >> >> >> -- >> Ing. Ivaldi Andres >> > > -- Ing. Ivaldi Andres
