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Tag: Spark

ParallelM Aims to Close the Gap in ML Operationalization

A startup named ParallelM today unveiled new software aimed at alleviating data scientists from the burden of manually deploying, monitoring, and managing machine learning pipelines in production. Dubbed MLOps, Parall Read more…

Snowflake Taps Qubole for Deep Machine Learning in the Cloud

Organizations storing big data in Snowflake's cloud data warehouse can now run machine learning and deep learning algorithms against that data thanks to a new partnership with Qubole. The two companies today announced Read more…

Dr. Elephant Leads the Performance Parade

I started working on big data infrastructure in 2009 when I joined Cloudera, which at the time was a small startup with about 10 engineers. It was a fun place to work. My colleagues and I got paid to work on open source Read more…

Databricks Puts ‘Delta’ at the Confluence of Lakes, Streams, and Warehouses

Databricks today launched a new managed cloud offering called Delta that seeks to combine the advantages of MPP data warehouses, Hadoop data lakes, and streaming data analytics in a unifying platform designed to let user Read more…

Containerized Spark Deployment Pays Dividends

Hadoop has emerged as a general purpose big data operating system that can perform a range of tasks and run all kinds of processing engines. But all that power and flexibility comes with a cost, which is something that o Read more…

DataRobot Reaches Out to SAS, Financial Services

Companies that use DataRobot's software to automate data science tasks can now output models directly from SAS, the dominant analytics company whose software is widely deployed in enterprises around the world. The upstar Read more…

Taking the Data Scientist Out of Data Science

If you were a data scientist three years ago, you could pretty much write your own ticket. Everybody in the industry, it seemed, either wanted to hire a data scientist, or wanted to be one. But today, thanks to a conflue Read more…

IBM Bolsters Spark Ties with Latest SQL Engine

IBM is extending its commitment to Apache Spark as a key component of in-memory analytics with the latest release of its SQL engine for Hadoop. The new version of IBM Big SQL released last week also solidifies the com Read more…

Hadoop Engines Compete in Comcast Query ‘Smackdown’

Who rules the ring when it comes to Hadoop SQL query engine performance? Can flashy newcomers like Presto and Spark take an established giant like MapReduce to the matt? Comcast recently held a competition to crown the b Read more…

Yahoo’s Massive Hadoop Scale on Display at Dataworks Summit

Yahoo put its massive Hadoop investment on display this week at Dataworks Summit, the semi-annual big data conference that it co-hosts with Hortonworks. While Hadoop is no longer the conference headliner that it once Read more…

Hortonworks Shifts Focus to Streaming Analytics

Hortonworks started life providing a Hadoop distribution that allowed customers to process big data at rest. But these days, the company has shifted its much of its attention and resources to streaming analytics, or proc Read more…

Spark’s New Deep Learning Tricks

Imagine being able to use your Apache Spark skills to build and execute deep learning workflows to analyze images or otherwise crunch vast reams of unstructured data. That's the gist behind Deep Learning Pipelines, a new Read more…

Pepperdata Takes On Spark Performance Challenges

Apache Spark has revolutionized how big data applications are developed and executed since it emerged several years ago. But troubleshooting slow Spark jobs on Hadoop clusters is not an easy task. In fact, it may even be Read more…

Cloudera Unveils Altus to Simplify Hadoop in the Cloud

Running Hadoop, whether on-premise or in the cloud, is neither simple nor easy. Administrators with specialized skills are needed to configure, manage, and maintain the clusters for their clients, who are data scientists Read more…

Google/ASF Tackle Big Computing Trade-Offs with Apache Beam 2.0

Trade-offs are a part of life, in personal matters as well as in computers. You typically cannot have something built quickly, built inexpensively, and built well. Pick two, as your grandfather would tell you. But appare Read more…

Masking Technical Complexity in the Security Data Lake

Today's growing cybersecurity threat demands a sophisticated response, one that increasingly involves the utilization of big data technologies like parallel file systems and machine learning. However, some security exper Read more…

Iguazio Re-Architects the Stack for Continuous Analytics

When it comes to modern big data architectures, you will typically find lots of different components, engines, and moving parts, each of which tackles part of the problem. One vendor with bold vision of re-architecting t Read more…

Learning from Your Data: Essential Considerations

For any organization undergoing digital transformation, a primary consideration is how to find, capture, manage and analyze big data. They are looking to big data and data science to facilitate the discovery of analytics Read more…

Hortonworks Touts Hive Speedup, ACID to Prevent ‘Dirty Reads’

If you're considering using Hadoop for SQL-based analytics and BI, you'll be interested in the latest news out of Hortonworks, which today unveiled a new release of its flagship data platform that boasts a fast new relea Read more…

Meet Ray, the Real-Time Machine-Learning Replacement for Spark

Researchers at UC Berkeley's RISELab have developed a new distributed framework designed to enable Python-based machine learning and deep learning workloads to execute in real-time with MPI-like power and granularity. Ca Read more…

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