I’m using Redmine to manage projects and bug reports, I was needing a daily report with spent time by user on each project, nothing complicated, but I wanted a cross-reference result like Excel dynamic tables. As we know, MySQL doesn’t support dynamic cross-reference queries but I make an approach:

1. Write the main query with rows: project identifier, task subject and total hours in a date range.

SELECT p.identifier, 
        e.issue_id, i.subject, round(SUM(e.hours),2) AS total_hours
        FROM redmine_nsp.time_entries e
        INNER JOIN redmine_nsp.issues i ON e.issue_id = i.id
        INNER JOIN redmine_nsp.projects p ON e.project_id = p.id
        WHERE e.spent_on BETWEEN '2014-07-01' AND '2014-07-07'
 GROUP BY p.identifier,e.issue_id;

+------------+----------+----------------------------+-------------+
| identifier | issue_id | subject                    | total_hours | …

Get the best from both worlds with bundled packages: a training course and a certification exam voucher. You save 20% when you buy training and certification in discount packages.

Training helps you acquire product expertise. Certification proves this expertise to your future employers.

There are two MySQL Discount Packages: MySQL Database Administration and MySQL Developer.

For more information about the authentic MySQL curriculum, go to …

Well, currently I am into the third week of mongodb node course "M101JS: MongoDB for Node.js Developers" and I am pretty enjoying it.

Lots of personal learning into node and mongodb.

The third week subject of "Patterns, Case Studies & Tradeoffs" is really interesting.

Here is a list of topics, I learned about:
- Mongodb rich documents concept.
- Mongodb schema use cases.
- Mongodb one:one, one:many, many:many use cases.
- How to select schema based on the usage like whether you want max performance
  or it may be a tradeoff.

One important point, I learned during the course is:
"While relational databases usually go for the normalised 3rd form so that data usage is agnostic to application, but mongodb schema arrangement is very closely related to application usage and varies accordingly."

Optimization involves improving the performance of a database server and queries that run against it. Optimization reduces query execution time and optimized queries benefit everyone that uses the server. When the server runs more smoothly and processes more queries with less, it performs better as a whole. To learn more about how a MySQL developer can make a difference with optimization, take the MySQL Developers training course.

This 5-day instructor-led course is available as:

• Live-Virtual Event: Attend a live class from your own desk - no travel required. Choose from a selection of events on the schedule to suit different timezones.
• In-Class Event: Travel to an education center to attend an event. Below is a selection of the …

Introduction So here’s a recent requirement that I’ve just encountered. I have a shared MySQL database I have several users that I want them to be able to create new databases However, I don’t want them to see each other’s databases And just to be absolutely clear, I obviously don’t want to give them all […]

Background:

Prior to version 3.10, MySQL Enterprise Backup (MEB) used zlib compression for in-memory compression of datafiles. The compression worked by splitting the innodb datafiles into fixed size blocks and compressing each block independently.After searching on the web we found there are many compression algorithms available which can be used for compression. This triggered the idea of testing the performance of available compression algorithms. If the benchmark shows improved performance we can make backup and/or restore faster by adding the new compression algorithm to MEB.

Implementation :

The idea to implement the algorithms procceded as follows .

1. Select a "long list" of algorithms based on literature and what Google and other databases are using.
2. Create a prototype of MEB supporting the algorithms in the long list.
3. Run comparison tests of algorithms with the MEB …

The MySQL Utilities Team is pleased to announce the latest release candidate (RC) release of MySQL Utilities. This release includes a number of improvements for useabilty, stability, and a few enhancements. A complete list of all improvements can be found in our release_notes.

New Utilities!
We have also included two new utilities.

• The mysqlrplsync utility was added, which checks data consistency between servers in a replicated setup. 
• The mysqlrplms utility was added, which provides round-robin multi-source replication (a slave server continually cycles through multiple masters in order to store a consolidated data set).

How Can I Download MySQL Utilities?
You can download MySQL Utilities 1.4.2 from the following link using one of the pre-built …

I've completed a new release of the Connector/Arduino! The new release contains some major improvements with memory handling.

• The library has been trimmed to save memory.
  • Static strings moved to PROGMEM strings
  • Unused structures removed (e.g. ok_packet)
  • Moved two more methods to optional compilation
• The WITH_SELECT is turned *OFF* by default. If you want to use select queries, be sure to uncomment this in the mysql.h file.
• Added a CHANGES.txt file to track changes between releases.

Memory, What Memory?
If you have used previous versions of the connector in medium to large sketches or have long query strings or even many variables, chances are you have hit the memory limit for your wee Arduino board.

This can manifest itself in a number of ways. Most notably, the sketch may work …

Parallel replication is in MariaDB 10.0. I did some benchmarks on the code in 10.0.9. The results are quite good! Here is a graph that shows a 10-times improvement when enabling parallel replication:

The graph shows the transaction per second as a function of number of slave worker threads, when the slave is executing events from the master at full speed. The master binlog was generated with sysbench oltp.lua. When the binlog is enabled on the slave and made crash-safe (--sync-binlog=1 --innodb-flush-log-at-trx-commit=1), the slave is about ten times faster at 12 worker threads and above compared to the old single-threaded replication.

These results are for in-order parallel replication. With in-order, transactions are committed on the …

Data migrations always have a wide range of challenges. I recently took on a request to determine the difficulty of converting an ecommerce shop's MySQL 5.0 database to PostgreSQL 9.3, with the first (presumably "easier") step being just getting the schema converted and data imported before tackling the more challenging aspect of doing a full assessment of the site's query base to re-write the large number of custom queries that leverage MySQL-specific language elements into their PostgreSQL counterparts.

During the course of this first part, which had contained a number of difficulties I had anticipated, I hit one that I definitely had not anticipated:

ERROR:  value too long for type character varying(20)

Surely, the error message is absolutely clear, but how could this possibly be? The obvious answer--that the varchar definitions were different lengths between MySQL and PostgreSQL--was sadly quite wrong (which you knew, …