Release Note 20161201

This is a summary of new features and improvements introduced in the December 1, 2016 release. If you have any product feature request, please file it at feedback.treasuredata.com.

Table of Contents

Workflow: Treasure Workflow Public Access

We have been providing Treasure Workflow feature to limited customers last 6 months, and happy to announce it’s now available for public access. Treasure Workflow enables you to build repeatable data processing pipeline.

Here’s one of the quote from early workflow user, Packlink.

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Thanks to Treasure Workflow, we’ve been able to make our entire data pipeline stable and reliable. We pull data from Salesforce, Zendesk, Elastic, MySQL, MongoDB, consolidate them all without worrying about quality delays, organize our analytic steps, and then send the results to Tableau, Salesforce, and other business & data systems.” - Pierre Bevillard, Head of Business Intelligence at Packlink.”

Please follow the documentation below to start making your data pipeline more reliable!

Integration: Apache Spark Driver (Private Alpha)

We have released Apache Spark Driver as private alpha. This driver allows your Spark cluster to access data stored within Treasure Data.

scala> import com.treasuredata.spark._
scala> val td = spark.td
scala> val d = td.df("sample_datasets.www_access")
scala> d.show
+----+---------------+--------------------+--------------------+----+--------------------+----+------+----------+
|user|           host|                path|             referer|code|               agent|size|method|      time|
+----+---------------+--------------------+--------------------+----+--------------------+----+------+----------+
|null|136.162.131.221|    /category/health|   /category/cameras| 200|Mozilla/5.0 (Wind...|  77|   GET|1412373596|
|null| 172.33.129.134|      /category/toys|   /item/office/4216| 200|Mozilla/5.0 (comp...| 115|   GET|1412373585|
|null| 220.192.77.135|  /category/software|                   -| 200|Mozilla/5.0 (comp...| 116|   GET|1412373574|
+----+---------------+--------------------+--------------------+----+--------------------+----+------+----------+
only showing top 3 rows

This article explains how to use Treasure Data’s Apache Spark Driver from Amazon Elastic MapReduce (EMR).

Please note that this feature is in alpha stage, and the access is disabled by default. We’re looking for customers who know Apache Spark well and are willing to try this feature and give feedbacks to our team.

If you’re interested in, please contact product@treasure-data.com.

Input: PostgreSQL Data Connector Incremental Improvement – Timestamp Support

You can now incrementally pull data from PostgreSQL databases using columns of Timestamp type.

Input: MySQL Data Connector Incremental Improvement – Datetime & Timestamp Support

You can now incrementally pull data from MySQL databases incrementally using Datetime & Timestamp type columns.

Output: Result Output to Microsoft SQL Server

Now you can export Treasure Data’s query result into Microsoft SQL Server.

Output: Result Output to AudienceOne

Now you can export Treasure Data’s query result into AudienceOne public DMP (Data Management Platform).

Collection: iOS SDK v0.1.21

iOS SDK v0.1.21 was released. This fixes a bug when you use the SDK from Swift.

Collection: Unity SDK v0.1.7

Unity SDK v0.1.7 was released. This release upgraded internall iOS / Android SDK verion. Everyone is recommended to upgrade.

Toolbelt: CLI v0.15.2

We have deprecated Pig engine as we announced.


Last modified: Dec 05 2016 06:14:22 UTC

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