The 5-Minute Series : Downloading your Koha SQL Report

Presenting a fast and flexible option to download your report.

One of the best things about Koha is the complete freedom it provides its users to create a custom SQL report of any level or degree of complexity as long as the query is compliant to MySQL SQL syntax – reports like e.g. accession registers, detailed circulation statistics etc.

Of course, once you have your report, if you are anything like *us*, you would want to grab the data and the do further analysis or use it to make that fancy-schmancy report or use a part of it in a presentation. Of course to do any of that, the data has to be downloaded locally. Koha provides you with three (03) options:

  1. As comma separated value (.CSV) file
  2. As a tab separated (.txt) file
  3. As OpenDocument Spreadsheet (.ODS) file

Now, if you are an / LibreOffice user, you may be tempted to go for the third option i.e. download the data as an .ods file. While this may look like the best option. It is *not* always so. The biggest problem is that if your report returns a lot of records, then generating the .ODS file is going to take a bit of time. Also, if your system is low on RAM, this can get *really* slow.

On the other hand, the files in .CSV and the .TXT formats are generated and downloaded almost instantly OR at least faster in comparison by several order of magnitude! Given that, which one among the two are your best bet? Well, in our considered opinion, the tab-separated .TXT file is the best. Here is why: if the single quotes in your data are not properly escaped, then your CSV data may be misinterpreted due to the un-escaped single-quote. leading it to split the data that should have been together into separate columns during an import. In contrast, a “tab separated” file will usually work without any issue unlike the CSV file.

So, if you want the data download to be fast and easy to split into columns correctly, the tab-separated .TXT file provides us the best overall option.

FMIRO CCU’s public z39.50 server running on Koha ILS achieves 100% reliability on IRSpy.

Hosted by L2C2 Technologies, FMIRO becomes the 5th Indian entry into IRSpy’s global z39.50 directory.

We are happy to announce the z39.50 service of FMIRO CCU (FOSMA Maritime Institute & Research Organisation, Kolkata branch) has achieved 100% reliability as an open access z39.50 search target for bibliographic materials related to maritime and ship operations. With this, FMIRO CCU becomes the fifth publicly announced z39.50 server from India which is listed on IRSpy service provided by Index Data.

FMIRO CCU’s nascent library is hosted on L2C2 Technologies‘s cloud platform using Koha ILS. The FMIRO OPAC is available at : The collection at FMIRO is a specialized collection focused solely on topics related to maritime, marine engineering, ship building, ship operations and nautical sciences. It is still a very small collection that is quite literally growing by the day.

Host connection reliability

Host connection reliability measures the reliability of the target only in its ability to respond to connections: the display indicates the number of successful connections in the last two months, the total number of attempted connections in that time, and the percentage of successful connections. For example, reliability of 9/15 = 60% indicates that fifteen attempts have been made to connect to the server in the last two months, of which nine (60%) have been successful. [1]

About IRSpy

IRSpy maintains a global registry of information retrieval targets, about 1295 as per recent count (, supporting protocols like ANSI/NISO Z39.50 (ISO 23950) and SRU/SRW web services.

About Index Data

Short answer: The guys who publish the Zebra indexing engine and YAZ toolkit and software libraries.

Long answer: Since 1994, Index Data has offered software development, consulting and integration with a focus on search. Our pioneering involvement in open source and open standards dates back to the first release of the YAZ toolkit for Z39.50 in 1995. [2]


[1] IRSpy help: info/reliability

[1] About Index Data