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A C language case study is presented "Conjunctive Selection Conditions in Main Memory", Kenneth A. Wood, DBMSs on a Modern Processor: Where Does Time Go?, Proceedings of the 25th International Conference on Very Large Data Bases", p.266-277, September 07-10, 1999. Theoretical background for simple SELECTS with WHERE clauses can be derived from the article "Anastassia Ailamaki, David J. But partitioning gives good performance boost, especially when partitioning over 3 dimensions. There is always a full-table scan, so indexes provide only little help. Due to the "Multidimensional Hierarchical Clustering" all SQL statements are simple SELECT SUM(measure) with a range WHERE clause for each dimension. Even if there are multiple tables, there is no "star schema", no GROUP BY and no JOINS. The main difference to the closest Open Source OLAP project - Mondrian a.k.a Pentaho, is the fact that Cubulus does all the aggregations inside the relational database (by generating multiple queries). Dr Volker Markl expressed in mail his consent to use the range clustering in an OSS project. Database Engineering and Applications Symposium, pp. Bayer: Improving OLAP Performance by Multidimensional Hierarchical Clustering. OLAP aggregation engine uses "hierarchical range-clustering of keys" (read "V. It is in early-alpha, none the less it can already show aggregated measures across hierarchical dimensions. Hi, There is a new Open Source OLAP project, called Cubulus OLAP. I'll have to redo my testing and to see what happened to the performance. The real good news is that the partition maintenance commands all worked with InnoDB! Dropping & Reorganizing partitions worked perfectly. Queries that ran on the partitions were about the same performance wise as those on the unpartitioned table. Performance, surprisingly wasn't what I expected. The plan is to use the ALTER TABLE REORGANIZE PARTITION statement to merge the older partitions together once per day, and to add a new partition once per day.Īfter the data was reloaded, it was time to test the performance, and the ability to add partitions and reorganize them (this was broken in version 5.1.11-beta). I need to keep a rolling 60 days of daily partitions active. There are a lot of partitions that I have defined. PARTITION P20061130 VALUES LESS THAN (TO_DAYS('')) PARTITION P20061003 VALUES LESS THAN (TO_DAYS('')), PARTITION P20061002 VALUES LESS THAN (TO_DAYS('')),
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PARTITION P20061001 VALUES LESS THAN (TO_DAYS('')), PARTITION P200609 VALUES LESS THAN (TO_DAYS('')), PARTITION P200602 VALUES LESS THAN (TO_DAYS('')), PARTITION p200601 VALUES LESS THAN (TO_DAYS('')), PARTITION p2005 VALUES LESS THAN (TO_DAYS('')), KEY `ix_nsdl_ymdh_entity_seller` (`ymdh`,`entity_id`,`seller_entity_id`) KEY `ix_nsdl_ymdh_entity_buyer` (`ymdh`,`entity_id`,`buyer_entity_id`), KEY `ix_nsl_ymdh_buyerli` (`ymdh`,`buyer_line_item_id`), `id` int(10) unsigned NOT NULL default '0', `ymdh` datetime NOT NULL default ' 00:00:00', `frequency` smallint(6) NOT NULL default '0', `pub_learn_type` char(1) NOT NULL default '', `adv_learn_type` char(1) NOT NULL default '', `is_adjustment` tinyint(4) NOT NULL default '0', `country_group_id` int(11) NOT NULL default '0',
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`pop_type_id` int(11) NOT NULL default '0', `seller_line_item_id` int(11) NOT NULL default '0', `seller_entity_id` int(11) NOT NULL default '0', `buyer_line_item_id` int(11) NOT NULL default '0', `buyer_entity_id` int(11) NOT NULL default '0', `entity_id` int(11) NOT NULL default '0', This is what the new table schema looks like with partitioning: I set innodb_open_files to 1000 based on the tables and partitions I plan on supporting. I made some minor changes to the configuration for partitioning, namely innodb_file_per_table and innodb_open_files. First order of business, convert the existing table schema to one that supports partitioning. Finally, it's time to start putting MySQL 5.1.12-beta through the wringer.