The Impala project has already passed several important milestones on the way to its status as the leader and open standard for BI and SQL analytics on modern big data architecture. Today’s milestone is the submission of proposals for Impala and Kudu to join the Apache Software Foundation (ASF) Incubator.
[Update: Read the text of the Impala and Kudu proposals here and here, respectively.]
Since its initial release nearly five years ago,
This year will close out with new features for reliability, usability, and nested types, and in 2016, performance-related enhancements promise >20x gains.
It’s been roughly a year since we provided an update about the Impala roadmap. During that time, a number of milestones have been reached:
- Most Cloudera customers have deployed Impala to production across industries including financial services, retail, healthcare, gaming, government, advertising, and telecom.
In the conclusion to this series, learn how resource tuning, parallelism, and data representation affect Spark job performance.
In this post, we’ll finish what we started in “How to Tune Your Apache Spark Jobs (Part 1)”. I’ll try to cover pretty much everything you could care to know about making a Spark program run fast. In particular, you’ll learn about resource tuning, or configuring Spark to take advantage of everything the cluster has to offer.
Security architecture is complex, but these testing strategies help Cloudera customers rely on production-ready results.
Among other things, good security requires user authentication and that authenticated users and services be granted access to those things (and only those things) that they’re authorized to use. Across Apache Hadoop and Apache Solr (which ships in CDH and powers Cloudera Search), authentication is accomplished using Kerberos and SPNego over HTTP and authorization is accomplished using Apache Sentry (the emerging standard for role-based fine grain access control,
With Kafka now formally integrated with, and supported as part of, Cloudera Enterprise, what’s the best way to deploy and configure it?
Earlier today, Cloudera announced that, following an incubation period in Cloudera Labs, Apache Kafka is now fully integrated into Cloudera’s Big Data platform, Cloudera Enterprise (CDH + Cloudera Manager). Our customers have expressed strong interest in Kafka, and some are already running Kafka in production.