Apache Spark

This blog covers new benchmark tests to better understand Autoscaling behaviour of concurrent Apache Spark applications. We believe that this will help in advancing research… The post Apache Spark...

The sixth release of Apache Sqoop i.e. 1.4.7 is out! This is one of the most significant updates to the Sqoop platform. We give you… The post Apache Sqoop 1.4.7 – 9 reasons why you need it...

Qubole improves the performance of Spark workloads with enhancements such as fast storage, distributed caching, advanced indexing, metadata caching, job isolation on multi-tenant clusters. Watch here

Ensighten was able to decouple their compute from storage and handle user-level management and permissions across a variety of Spark, Hadoop and Presto with Qubole

AgilOne runs a variety of workloads for querying data, running ML models, orchestrating ML workflows, and more on Qubole

Nauto Improves its Data Scientist Prodcutivity, Accelerates Product Development

TrafficGuard relies on big data processing to detect and prevent ad fraud, which requires a robust infrastructure.

Self-paced guide to the Apache Spark analytics engine using Qubole

Automatically use the S3 Select service whenever applicable to speed up queries

Build and use a time-series analysis model to forecast future sales from historical sales data

Significantly improve the overall performance of running Hadoop-based engines on the cloud object store

How Dynamic Filtering in Spark dramatically improves the performance of Join Queries

How RubiX differs from Spark’s internal cache, and its performance improvement for Spark workloads

Direct Writes delivers performance improvements of up to 40x for write-heavy Spark workloads

Introducing sparklens.qubole.com, a reporting service built on top of Sparklens to lower the pain of sharing Sparklens output

Run large Apache Spark clusters on the cloud without fear of job loss or out-of-control cloud costs