Articles & News

01 April 2020

Hue Active Users Metric Improvements

To understand the performance of Hue, we want to know how many active users in Hue–and more specifically–how many on each host. An active user is who sends requests from his/her browser to the Hue server in the last one hour. Recently, Hue got some improvements for providing and displaying better metrics. On premise, Hue is using PyFormance implements /desktop/metrics endpoint. Cloudera Manager collects data via the endpoint and displays the metric “Active Users” in the Charts Library, but all hosts show the same number of active users.…

2 minutes read - Version 4 / Development

27 February 2020

Re-using the JavaScript SQL Parser

SQL autocompletion The parser is running on the client side and comes with just a few megabytes of JavaScript that are then cached by the browser. This provides a very reactive & rich experience to the end users and allows to import it as a module dependency. While the dynamic content like the list of tables, columns.. is obviously fetched via remote endpoints, all the SQL knowledge of the statements is available.…

3 minutes read - Version 4 / Development

24 September 2019

Introducing Hue requests tracing with Opentracing and Jaeger in Kubernetes

Hue is getting easy to run with its Docker container and Kubernetes Helm package. Recent blog posts describes how to get access to logs and metrics. Even in a non distributed world it can get noisy to know how much time is being spent where in each user request. Consequently, in the context of a Data Analyst, knowing why a certain query is slow can become problematic. On top of that, adding multiple tenants and users, and more than 20 external APIs and the fog about fine grain performances appears and its becomes extremely manual and time consuming to troubleshoot.…

3 minutes read - Version 4 / Development

19 July 2019

BYOA – Build Your Own Autocompleter

Hue is a SQL Editor integrating with the most common data warehouses and databases. Getting specialized autocomplete for each language brings better code maintainability (force a decoupled design), speed (no need to load all the parsers for only one language) and obviously a nicer end user experience (Impala, Hive, PostgreSQL… always have slight different syntax). In Hue we use generated parsers to handle autocomplete and syntax checking in the editors. In this post we’ll guide you through the steps necessary to create an autocompleter for any SQL dialect in Hue.…

8 minutes read - Version 4 / Development

22 July 2016

Login into Hue using the Python Request library

In this little snippet we will show you how to login into HUE using python requests library. Hue is based on the Django Web Framework. Django comes with user authentication system. Django uses sessions and middleware to hook the authentication system into request object. HUE uses stock auth form which uses “username” and “password” and “csrftoken” form variables to authenticate. In this code snippet, we will use well-known python “requests” library.…

2 minutes read - Development

19 July 2016

Change your maps look and feel

Did you know that you can change the look and feel of your Hue maps just by specifying two extra variables on the Hue configuration? Here above the default style of Hue's maps; we use the open source library Leaflet to draw them. They also did a great job putting together a list of map providers that can be used in Hue as well:</a>. Let's display the Esri.…

1 minute read - Development

04 May 2016

The Hue team development process

Hello potential Hue developers! 🙂 We want to share with you the development process we've been refining during the past years. This is what makes the Hue team ultra fast and efficient. Ready? Go! All the changes (new features, improvements, bugs) need to be tracked. We use JIRA. The changes should have a pseudo-mnemonic short ID (ie: HUE-123). That comes for free on JIRA but it requires a bit of programming on other systems.…

3 minutes read - Development

27 October 2015

Hue performance tuning guide

Last update Aug 30th 2018 Latest A major improvement in 4.2 is IMPALA-1575, meaning that Impala queries not closed by Hue have their resources actually released after 10min (vs never until then). This is a major improvement when having many users. It is worth the upgraded even just for this one. Hue in 4.2 got 500+ bug fixes. Hue also now comes with caching of SQL metadata throughout all the application, meaning the list of tables or a database or the column description of a table are only fetched once and re-used in the autocomplete, table browser, left and right panels etc.…

3 minutes read - Development

21 October 2015

How to use the Livy Spark REST Job Server API for submitting batch jar, Python and Streaming Jobs

Livy is an open source REST interface for interacting with Spark from anywhere. It supports executing snippets of code or programs in a Spark Context that runs locally or in YARN. Note: Livy is not supported in CDH, only in the upstream Hue community.  We previously detailed how to use the interactive Shell API (aka spark shells) and how to create remote shared RDDs. In this follow-up we will see how to execute batch jobs (aka spark-submit) in YARN.…

7 minutes read - Development

13 October 2015

How to use the Livy Spark REST Job Server API for sharing Spark RDDs and contexts

Livy is an open source REST interface for interacting with Apache Spark from anywhere. It supports executing snippets of Python, Scala, R code or programs in a Spark Context that runs locally or in YARN. In the episode 1 we previously detailed how to use the interactive Shell API. In this follow-up, lets put the API in practice for a more concrete example: let's simulate sharing RDDs or contexts!  Starting the REST server This is described in the previous post section.…

4 minutes read - Development

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