by alxtoth
OLAP aggregation engine with MDX support, web interface (slice & dice) and relational database backend. See "Documentation" for more. Presentation: http://cubulus.sourceforge.net/. See online demo courtesy of Webfaction, http://alxtoth.webfactional.com
-fix Adobe SVG plugin for Iexplorer -fix SVG rendering error for empty charts -fix content-type header = "application/xhtml+xml"
-iframe with chart has static height to fix rendering problems in Firefox -fixed minor Javascript errors, now works fine in Firefox, Camino, Safari
-added SVG charts
New feature: hierarchical charts. The vertical boxes represent hierarchy "on rows", horizontal boxes represent datasets "on columns" scaled to the "on rows" measure. (See the online demo at http://alxtoth.webfactional.com ). ...
bugfix: etl.py not aware of metadata.is_table (split fact table)
-bugfix: rounding broken for MonetDB -bugfix: keeping drillpath when dicing -bugfix: gen.py generates all tables
-performance improvement: split fact table by non-agregatable dims -gen.py: generate split fact tables, MonetDB compatible SQL -bugfix: unionAllSQL had empty rowL when workload divisible with MAX_PIPELINED_UNION -bugfix: unionAllSQL failed when selecting ...
Currently Cubulus scaling status is: "scale up approach" = use multiple Python threads for running SQL queries. Works in theory: one single core CPU runs all the threads. Practical result: it does not crash under Apache Bench stress testing ...
MonetDB ( http://monetdb.cwi.nl/ ) database is cca 10 to 15 times faster than MySQL (partitioned, no indexes) in regards to Cubulus queries. This is due to Monet being a "column-oriented" database. I don't mean to start a benchmarking ...
-bugfix: needed to press "execute MDX" twice -bugfix: time measurement -experimental support for MonetDB; only works on Windows
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