This new open source complement to HDFS and Apache HBase is designed to fill gaps in Hadoop’s storage layer that have given rise to stitched-together, hybrid architectures.
The set of data storage and processing technologies that define the Apache Hadoop ecosystem are expansive and ever-improving, covering a very diverse set of customer use cases used in mission-critical enterprise applications. At Cloudera, we’re constantly pushing the boundaries of what’s possible with Hadoop—making it faster,
This new core security layer provides a unified data access path for all Hadoop ecosystem components, while improving performance.
We’re thrilled to announce the beta availability of RecordService, a distributed, scalable, data access service for unified access control and enforcement in Apache Hadoop. RecordService is Apache Licensed open source that we intend to transition to the Apache Software Foundation. In this post, we’ll explain the motivation, system architecture,
Learn how to build an Impala table around data that comes from non-Impala, or even non-SQL, sources.
As data pipelines start to include more aspects such as NoSQL or loosely specified schemas, you might encounter situations where you have data files (particularly in Apache Parquet format) where you do not know the precise table definition. This tutorial shows how you can build an Impala table around data that comes from non-Impala or even non-SQL sources,
Recent Impala testing demonstrates its scalability to a large number of concurrent users.
Impala, the open source MPP query engine designed for high-concurrency SQL over Apache Hadoop, has seen tremendous adoption across enterprises in industries such as financial services, telecom, healthcare, retail, gaming, government, and advertising. Impala has unlocked the ability to use business intelligence (BI) applications on Hadoop; these applications support critical business needs such as data discovery,
Live updates about your query’s progress in the Impala Shell? That’s a win!
The Impala Shell is a great tool for quickly running exploratory queries, or testing new features in Impala. While Impala is pretty fast, some queries can still take several seconds or longer to complete. It’s therefore useful to be able to see how much progress the query has made and to get an idea of how long the query will take.