Azure HDInsight brings next generation Apache Hadoop 3.0
Preview of Apache Hadoop 3.0 in Azure HDInsight 4.0
Led by Hortonworks, Apache Hadoop 3.0 represents over 5 years of work across the community since the last major update to the Hadoop stack. Enterprises can now realize their data lake vision while efficiently incorporating deep learning frameworks in to their applications all on the same Hadoop stack that they are comfortable with.Some of the key enhancements include:
- With ACID semantics enabled by default, Apache Hive 3.0 becomes more like a traditional database, making it easier for customers to build LOB applications on top of very large data sets.
- Apache Druid is an open source data store with indexing/caching capabilities on top of a column-oriented storage layout. With Apache Hive and Apache Druid (now available by default), customers can do near real time exploratory analytics on incoming data.
- With Tensorflow, available by default, and GPU support, Apache Hadoop 3.0 squarely targets the machine learning and deep learning scenarios.
Enhanced enterprise grade security
Enterprise grade security and compliance is a critical requirement from all customers building big data applications that store or process sensitive financial, business, personal, and healthcare data in the cloud.With the general availability of the Enterprise Security Package (ESP) customers can now:
- Ensure that users authenticate to their HDInsight clusters using their corporate domain credentials.
- Ensure that users are subject to rich fine-grained access policies (authored and managed in Apache Ranger) as per their corporate data access policies.
- Ensure that all access to critical data are logged and available in Apache Ranger for subsequent audit or forensic analysis as needed.
Advanced Debugging Tools for HDInsight Spark developers
Developers, data scientists and analysts are already know that Azure HDInsight offers rich development and debugging capabilities in a tool of their choice; IntelliJ, Eclipse, VSCode, Jupyter and Apache Zeppelin notebooks etc.Microsoft has now stepped it up one more level! Debugging large distributed big data application running on hundreds of nodes is hard and time consuming. Microsoft is now bringing its decade long experience of running and debugging nearly billions of jobs to the open-source world of Apache Spark. Key enhancements include:
- Job graph with playback and heatmap identifying read/write bottlenecks.
- Job critical path analysis and visualization.
- Data skew detection and analysis.
- Job specific data management including data preview, download, and copy.
Availability of key ISV applications on Azure HDInsight
Azure HDInsight supports a vibrant application ecosystem with the most popular big data applications available on Azure Marketplace. Customers will now find three new applications that they can use with Azure HDInsight covering key areas such as data governance, SQL-friendly queries over big data and application migration to Azure:- Starburst: Presto connectors on Azure HDInsight scales on demand and integrates other data sources with HDInsight.
- Waterline Data: A data cataloging and governance solution used by several Azure customers.
This is just the start. There are lot more updates coming to Azure HDInsight soon. So, stay tuned!
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