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Tableau public download 10.33/16/2024 Figure 1 is an example dashboard from the performance recorder, showing the time required to create an extract.įigure 2 – The benchmarks used in this work. The Tableau performance recorder was used to accurately determine the time needed to create the extracts (*.tde and *.hyper). This means there were 32 tests completed, but the actual number was closer to 50 due to sensitivity testing I completed. I also had to load each benchmark file into Tableau 10.5 to generate the hyper extracts. Since the computer I used for the current testing is different than what I used in Nov 2013, I had to run the benchmarks through Tableau 10.3.6 to get updated times for creating the Tableau data extracts. Information about these examples will be provided below. I was interested to see how the hyper engine responded to things like files that have a lot of null fields, wide columns, complicated text fields, or a lot of repetitive fields. These csv files originated from different projects and industries and each has different characteristics. To answer my question, I used 16 different real-world data sets. It is free and it motivates me to continue writing, so thanks!Įnter your email address to subscribe to this blog and receive notifications of new posts by email. If you like this article and would like to see more of what I write, please subscribe to my blog by taking 5 seconds to enter your email address below. This question will be answered after this article is published and I have more time to develop test cases. The third part of the mission is to see if the hyper engine leads to a better Tableau experience in terms of quicker responses when rendering large data sets. The second part of my mission is to examine the file compression that is achieved in the extracts. I really want to know if the “hype” around the “hyper” engine is real. How fast does Tableau read data from a character-separated file (*.csv) to produce a Tableau Data Extract (*.tde) file and a Hyper Data Extract (*.hyper)? The specific question I wanted to answer is: Now in 2018, I felt like revisiting the series of benchmark examples I established for Tableau to see how fast the new “hyper” data engine is compared to the pre-existing Tableau Data Engine. The first time I did this work was in November 2013. The Original Work and Four and A Half Years Later Once I decide to do something, however, I have to finish the work. I have always liked to benchmark computer programs, at least I thought I did! The work I show in this article took much longer than I expected it would, which effectively reduced the fun factor.
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