# DSS 1.4 Relase notes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#dss-1-4-relase-notes "Permalink to this headline")

* Version 1.4.5 - June 23rd, 2015

+ Important notes about migration

+ New features

+ Bug fixes

* Version 1.4.4 - March 30th, 2015

+ Important notes about migration

+ New features and enhancements

+ Bug fixes

* Version 1.4.3 - March 4th, 2015

+ Important notes about migration

+ Bug fixes

* Version 1.4.2 - February 17th, 2015

+ Important notes about migration

+ New features

+ Bug fixes

* Version 1.4.1 - January 29th, 2015

+ Important notes about migration

+ New features

+ Bug fixes

* Version 1.4.0 - January 13th, 2015

+ Important notes about migration

+ New features

+ Other enhancements

+ Major bugfixes

## Version 1.4.5 - June 23rd, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-5-june-23rd-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#important-notes-about-migration "Permalink to this headline")

Please see the release notes for 1.4.0

### New features[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#new-features "Permalink to this headline")

* Added support for Hive 1.1

### Bug fixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#bug-fixes "Permalink to this headline")

* Fixed FTP listing for WS\_FTPD

* Fixed Apache log file format

* Fixed “Last value” in grouping recipe

* Updated CentOS IUS repository URL

## Version 1.4.4 - March 30th, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-4-march-30th-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id1 "Permalink to this headline")

Please see the release notes for 1.4.0

### New features and enhancements[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#new-features-and-enhancements "Permalink to this headline")

* Official support for Oracle has been added.

* Amazon Linux 2015.03 is now supported.

### Bug fixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id2 "Permalink to this headline")

#### Data preparation[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#data-preparation "Permalink to this headline")

* Fixed Python processors in recipes over filesystem datasets (happened when no custom variables and no contribs were used)

#### Datasets and formats[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#datasets-and-formats "Permalink to this headline")

* Fixed ORC files with Hive 0.14+

* Fixed explore in the Twitter dataset

* Improved detection of Shapefiles and fixed support for uppercase-named shapefiles

* Fixes on SAS format parser

## Version 1.4.3 - March 4th, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-3-march-4th-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id3 "Permalink to this headline")

Please see the release notes for 1.4.0

### Bug fixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id4 "Permalink to this headline")

#### Recipes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#recipes "Permalink to this headline")

* An issue with running grouping recipe on non-SQL datasets has been fixed

* Running SQL script recipes on PostgreSQL could fail depending on how the “psql” binary is implemented

* Running SQL script recipes on PostgreSQL could loose the return code and all recipes always appeared to succeed whereas they did not

* Reading datasets in R when the schema contains comments has been fixed

#### Datasets[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#datasets "Permalink to this headline")

* Initial download of data in HTTP datasets has been fixed

#### Misc[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#misc "Permalink to this headline")

* The job screen now properly automatically refreshes

* Fixed an issue with Websockets and very long log messages

## Version 1.4.2 - February 17th, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-2-february-17th-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id5 "Permalink to this headline")

Please see the release notes for 1.4.0

### New features[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id6 "Permalink to this headline")

* A new processor has been added: “Generate combinations of numerical variables”

* New dataset: “FTP (no cache)”, which allows both read and write on FTP and does not cache input data. (see FTP)

* DSS now supports proxies for outgoing connections (FTP, HTTP, S3, Twitter). See /installation/custom/reverse-proxies)

* Hadoop: Support for HDP 2.2 has been added

### Bug fixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id7 "Permalink to this headline")

* Python’s write\_with\_schema could fail on some configurations of SQL output datasets

* Installation of plugins on Mac OS X without JDK has been fixed

* An issue has been fixed when running Impala on a Kerberos-enabled Hadoop cluster

* Exception reporting has been improved in the Machine Learning part

* Several issues have been fixed in the UI for New Cassandra Dataset.

* Support for `\r` as End-Of-Line marker has been added for CSV datasets

## Version 1.4.1 - January 29th, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-1-january-29th-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id8 "Permalink to this headline")

Please see the release notes for 1.4.0

### New features[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id9 "Permalink to this headline")

* A new reshaping processor has been added: “fold the keys of an array”

### Bug fixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id10 "Permalink to this headline")

#### Hadoop support[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#hadoop-support "Permalink to this headline")

* Fixed compatibility with MapR 4.0

* Support for MapR 2.0 and 3.0 has been removed

#### Machine learning[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#machine-learning "Permalink to this headline")

* Fix failures in prediction recipes with textual features

#### Python[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#python "Permalink to this headline")

* SQL code executed in Python recipes is now be properly streamed, even for very large result sets

#### Flow[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#flow "Permalink to this headline")

* Various UI bugfixes and improvements on the grouping recipe

* A bug has been fixed on the TimeRange dependency for MONTH-based partitioning

* A leak of file handles has been fixed in the backend <-> job communication, which could lead to “too many open files” errors

#### Misc[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id11 "Permalink to this headline")

* Support for Firefox 35.0 has been improved - However, pan and zoom in Flow on Firefox 35.0 remains slow

* Some documentation links have been fixed

## Version 1.4.0 - January 13th, 2015[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#version-1-4-0-january-13th-2015 "Permalink to this headline")

### Important notes about migration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id12 "Permalink to this headline")

The automatic data migration procedure is documented in Upgrading a DSS instance

As usual, we **strongly recommend** that you perform a full backup of your Data Science Studio data directory prior to starting the upgrade procedure.

Automatic migration of data from Data Science Studio 1.3.X is supported, with the following restrictions and warnings:

* The “dip.flow.activities.nthreads” parameter in dip.properties has been removed. Setting the number of activities is now done in the Administration pages (Settings > Build).

* Referencing a dip.properties entry from a FS dataset path is not possible anymore. Use the variables expansion system.

For migrations from Data Science Studio 1.2.X, please also see the release notes of version 1.3.0

### New features[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id13 "Permalink to this headline")

#### Mac OS X[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#mac-os-x "Permalink to this headline")

* DSS is now available on Mac OS X (10.9 and above).

* Note that the OS X version is only available for experimentation and evaluation purpose, it is not supported for production usage

* Download and install Mac OS X version from: http://www.dataiku.com/dss/editions/community-download/

#### Security[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#security "Permalink to this headline")

* You can now connect DSS to your corporate LDAP directory and use your LDAP users and groups to control access to DSS.

See Configuring LDAP authentication.

* DSS can now interact with Kerberos-enabled Hadoop clusters

See Connecting to secure clusters.

#### Visual data preparation[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#visual-data-preparation "Permalink to this headline")

* Transformation recipes created with the visual data preparation tool can now fully run on a Hadoop cluster. See Execution engines

* BETA feature: geo processing processors (see Geographic processors)

* Reverse geocoding (from GPS coordinates to city / region / country)

* Zipcode-based geocoding (from zipcode to GPS coordinates)

#### Data Visualization[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#data-visualization "Permalink to this headline")

* You can now export charts built with DSS as Excel documents for easy embedding

* Several color palettes are now available for charts. Furthermore, you can add custom color palettes

* BETA feature: geo charts (see Map Charts)

* Geo charts allow you to aggregate a dataset based on a column containing geo coordinates.

* Aggregation is made by administrative boundaries (city / region / country)

#### New data transformation recipes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#new-data-transformation-recipes "Permalink to this headline")

* “Grouping” recipe: new visual tool to perform grouping and aggregations (sum, avg, first, last, …)

* Multi-key grouping and multi-aggregations

* Integrated filtering

* Automatically runs in-database or on-Hadoop when possible.

* “Split” recipe: split one input dataset into several output datasets based on the value of a column or advanced rules

#### Datasets[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id14 "Permalink to this headline")

* Support for GeoJSON files

* Support for ESRI Shapefiles

#### Collaboration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#collaboration "Permalink to this headline")

* DSS now detects and warns when several users are working on the same dataset or recipe at the same time.

* Edit conflicts are automatically detected and avoided

#### Advanced usage[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#advanced-usage "Permalink to this headline")

* New Custom variables expansion system that allows you to use some shared and reusable variables in several parts of the Studio.

* You can now write custom Python code for advanced partition dependencies in Flow. See Specifying partition dependencies

* The number of concurrent running activities (builds of a partition) can now be set:

* per-job

* per-connection

* globally

* A command-line tool lets you mass-import all (or selected) tables of a Hive database as DSS datasets. See Hive

### Other enhancements[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#other-enhancements "Permalink to this headline")

#### Flow[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id15 "Permalink to this headline")

* When aborting a job, DSS tries to cancel running SQL queries and running Hadoop jobs

* Performance improvements for computing partition dependencies on large flows

* Partitioning variables substitution in code recipes can now either use $DKU\_XXX or ${DKU\_XXX} syntax

#### Visual data preparation[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id16 "Permalink to this headline")

* The “column split” processor can now either ignore or keep empty chunks

* The “regexp extractor” processor can now extract multiple matches

* New processor to duplicate a column

* New processors for advanced processing of complex content (JSON arrays and objects)

* New processor to bin the values of a numerical column

* “Live processing” charts can now work on a set of partitions

#### Web apps[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#web-apps "Permalink to this headline")

* You can now write a filtering formula to select a subset of rows in the JS webapp API

* Better syntax highlighting in the JS editor

* Code folding in all code editors

#### Data visualization[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id17 "Permalink to this headline")

* MIN and MAX are now available as aggregations in charts

* Legend can now be hidden

* Smoothing of lines and areas can now be disabled

#### Advanced usage[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id18 "Permalink to this headline")

* The Jython environment for custom processors now includes the “json” python package

#### Recipes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id19 "Permalink to this headline")

* The R API now supports sampling of the input datasets

#### Security[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id20 "Permalink to this headline")

* The “Administrator” information is now handled by groups instead of being a simple flag on the user.

#### Deployment[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#deployment "Permalink to this headline")

* Added support for RHEL 7 and CentOS 7

### Major bugfixes[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#major-bugfixes "Permalink to this headline")

#### Visual data preparation[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id21 "Permalink to this headline")

* Various issues around copy/paste in explore have been fixed

* “Analyse” will not give invalid data when Infinity appears in the column

* Parsing dates without any time information (only year/month/day) now properly respects the selected timezone

* When editing a preparation recipe, the “Custom format” form of the “Smart date” feature has been fixed

#### Data visualization[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id22 "Permalink to this headline")

* Several issues around “week” and “week of year” handling for timeline axis have been fixed

#### SQL notebook[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#sql-notebook "Permalink to this headline")

* Performance with large tables has been improved

* Error reporting has been improved

#### Datasets[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id23 "Permalink to this headline")

* Hidden / Useless files (like Hadoop success markers) are now properly ignored everywhere

* Counting records now works on MongoDB datasets

#### Machine learning[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id24 "Permalink to this headline")

* Training recipes now properly work on paritiotned datasets

* The “heatmap” in clustering results is now properly updated when switching between models

#### Collaboration[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id25 "Permalink to this headline")

* Cropping of transparent PNG for insights and projects icon now works properly

#### Misc[¶](https://doc.dataiku.com/dss/latest/release_notes/1.4.html#id26 "Permalink to this headline")

* An issue when changing the network of the host while DSS is running has been fixed
