Announcing Imply 2.2: Pivot Features Galore

May 16, 2017
Vadim Ogievetsky

Imply 2.2 adds new Pivot features that enhance filtering flexibility, especially for time filters, new percent of total measures, and tuning for approximate quantiles.Check out the screenshots below that show these new Pivot features in action.

Adding filters from the filter bar

You can now add filters directly from the filter bar.

This is particularly useful in interactive collections, where you can now add arbitrary filters.

Precise time picking

We have upgraded the Pivot time filter menu to allow you to select a precise time.

You can now also select several time ranges.

Percent of total measures

You can now configure measures that are defined as a percentage of their next higher split (or of the global total).

This in effect transforms the measures on the client side.

Tunable approximate quantiles

It is now possible to fine-tune approximateHistogram based quantiles, allowing you to determine your trade-off between performance and accuracy.

Enter a 3rd parameter in the quantile formula of the form 'resolution=400,numBuckets=10,lowerLimit=0,upperLimit=1000' to pass those tuning parameters to the underlying aggregator.

To understand how to tune the approximateHistogram parameters check out the Druid documentation

Query monitoring

Have you ever wondered what queries are being issued under the hood as you fly around your data? While it was been possible to run Pivot in verbose mode since the first release you can now inspect your queries directly from the UI.

The query view is a great way to understand how Pivot interacts with Druid in particular if you are utilizingcustom transformations or custom aggregations.

Other improvements

In addition to all of the above we also improved the consistency of some Pivot workflows as well as greatly reducing the number of queries that Pivot will issue to Druid.

And my favourite tiny feature in this release: the titles of the browser tabs will now show the names of the data cubes and collections.

Hope you enjoy.

Getting started

You can get the latest version of Imply on our download page. To learn more, please see our documentation. Any feedback, bug reports and feature requests are always welcome – you can post them in our user
group
or contact us.

Other blogs you might find interesting

No records found...
Jun 17, 2024

Community Spotlight: Using Netflix’s Spectator Histogram and Kong’s DDSketch in Apache Druid for Advanced Statistical Analysis

In Apache Druid, sketches can be built from raw data at ingestion time or at query time. Apache Druid 29.0.0 included two community extensions that enhance data accuracy at the extremes of statistical distributions...

Learn More
Jun 17, 2024

Introducing Apache Druid® 30.0

We are excited to announce the release of Apache Druid 30.0. This release contains over 409 commits from 50 contributors. Druid 30 continues the investment across the following three key pillars: Ecosystem...

Learn More
Jun 12, 2024

Why I Joined Imply

After reviewing the high-level technical overview video of Apache Druid and learning about how the world's leading companies use Apache Druid, I immediately saw the immense potential in the product. Data is...

Learn More

Let us help with your analytics apps

Request a Demo