Tableau Prep Slow

Tableau prep slow performance

In the same vein, too many cells in a table will slow things down considerably. Use action filters instead of quick filters. Action filters leverage the view itself as a filtering agent, saving it from having to query the entire dataset to populate the list. To create an action filter go to the menu and select DashboardActions. Consider doing data prep prior to developing a hyper-extract so will not have to do joins and filtering in Tableau which can be cumbersome and slow if there are many joins. Reporting tables or views can be created to pre-join the data which provides some flexibility in updating a Tableau Hyper-extract as new fields can be added without re.

Tableau Prep Slow

Best Practices and Methods for Improving Tableau Performance:

A dashboard with multiple worksheets can sometimes take longer to load. Below, I have listed some techniques and practices that will be very helpful in solving your dashboard performance issues. When the Tableau Server is very slow or Tableau Workbooks takes longer to load, you can follow these tips to sort out the performance issues.

Data

  • Use the Extract connection instead of the live connection to your data source.
  • Use the data source filter or use an extract connection to the data source.
  • Minimize the number of joins.
  • Analyze dimensions in new data sets using the Describe option.
  • Unused columns (measures/dimensions) should be removed to reduce loading time, custom SQL query time.
  • Use a common published TDS file for dashboard creation to prevent each team member from creating their own data source. Use common metadata for dashboard creation.
  • Use extracts connections wherever possible to improve performance.
  • Hide unused and confidential data items.
  • Roll up by aggregating or filtering to maintain the required data granularity.
  • Remove hierarchies for invisible dimensions.
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Filtering

Tableau Prep Slow Performance

  • Use fewer quick filters.
  • Do not choose complex ranges for quick filters options. It will slow down the query performance.
  • Minimize the use of multi-select, drop-down type lists in quick filters. It will take a long time to load and render.
  • Do not select specific values for quick filters. This will impact query loading time.

Custom SQL

  • Do not use custom SQL in live connections.
  • Use views to implement your custom SQL and try to connect Tableau to the view.
  • Do not use parameters in custom SQL in Tableau.
  • Tableau creates sub-queries for custom SQL, which will be very difficult for many databases to handle.
  • Try using views in the database or use multiple joins instead of using custom SQL.

Calculations

Tableau Prep Slow

  • Do not use calculations that requires data blending. The query will take a long time to load the data. Instead, try to use a view.
  • Do not use row-level calculations that use parameters

Rendering

Tableau Prep Slow Cooker

  • High usage of mark counts will increase the rendering time of Dashboards.
  • Do not use large file size images. This will increase the loading time.
  • Avoid using more no of custom shapes in the dashboard.

Dashboard Layout

  • Do not use multiple worksheets on a single dashboard.
  • While creating dashboards, fix the dashboard size as per the customer requirement. Avoid using automatic sizing for fixing dashboard size.

Tips for Working with 1M Rows

on August 5, 2013

Here at Tableau Public, we are so excited that all of our users have access to 1 million rows. We can’t wait to see what kind of stellar vizzes the community creates with ten times as many rows! But, before you dive right into all those beautiful rows of data, we have some tips to help you maximize performance of dashboards with such large datasets.

  • Extract, extract, extract! IRE members and our Public Premium customers may be using Tableau Desktop to build dashboards. If you are, making a data extract right away will make Tableau run a lot faster. If you are using the Tableau Public client, don’t worry, extracts are made automatically!
  • Minimize extract size. Hide unused fields and limit the extract size when you can. If your data source contains columns you don’t plan on using, don’t bring them in when you make your extract.
  • Everything in moderation. Don’t use too many quick filters. Don’t draw 400k marks in a view. Think about what is really necessary for your analysis.
  • If it ain’t fast in the program, it ain’t going to be fast online. If it is taking a long time to execute queries while you are building your dashboard, it will likely take a long time when it is published.
  • Be careful about how you use filters. Don’t use the “exclude” option, since Tableau will have to scan all the selected data whenever you change the filter. Avoid using the “individual dates and times” filter type for the same reason. If needed, use cascading quick filters for Years, Months and Days to show only the data that you are looking for.
  • Use Booleans. If and Case calculations are going to slow down performance. If you can, use a Boolean statement instead. For example, instead of a calculation that says:
    IF [Date]= TODAY() then “Today”
    ELSE “Not Today”
    END


    Try using:


    And alias “True” and “False” as “Today” and “Not Today”

  • Don’t use more marks than you need. Performance will suffer the more marks there are, so avoid plotting hundreds of thousands or marks. In the same vein, too many cells in a table will slow things down considerably.
  • Use action filters instead of quick filters. Action filters leverage the view itself as a filtering agent, saving it from having to query the entire dataset to populate the list. To create an action filter go to the menu and select Dashboard>Actions. Click the 'Add Action' button to create a filter.
  • Exclude all values when clearing a filter. When using a filtering action, select the “Clearing the selection will: Exclude all value”s. This checkbox avoids the potentially expensive query of asking for all of the data that the dashboard is able to render.
  • Pare down your multiple value filter lists. Having a huge list (100s-1000s) of options to filter by will make the list load slower. Try to bundle your categories into more broad groups. If you can’t group them, consider using a wildcard search to avoid having to load all of the options at once.
  • Don’t crowd your dashboard with too many views. Every view on a dashboard is another query that has to be sent to the data. If your dashboard is running slower than you’d like, consider moving some views to a different dashboard or combining a view views into combo charts.
  • Avoid long lists and tables. Text tables or views that have over 10k rows can really slow down processing. Reduce the number of rows with filters, or consider only showing the top/bottom 100.
  • Avoid lots of tabs. Every tab you add to your viz adds more time to the processing. If things are slow and your tabs are getting out of hand, consider breaking things up into multiple workbooks.
  • Don’t use “Fit to Window” dashboards. Starting with a common size for your dashboard not only makes doing layout easier and free from surprises; it also gives the server a better chance to re-use something in the cache across multiple views and requests. When choosing the size of your dashboard, use a size template or exact size instead of automatic.