Tag Archives: reliability

Offset Management For Apache Kafka With Apache Spark Streaming

Categories: CDH Kafka Spark

An ingest pattern that we commonly see being adopted at Cloudera customers is Apache Spark Streaming applications which read data from Kafka. Streaming data continuously from Kafka has many benefits such as having the capability to gather insights faster. However, users must take into consideration management of Kafka offsets in order to recover their streaming application from failures. In this post, we will provide an overview of Offset Management and following topics.

  • Storing offsets in external data stores
    • Checkpoints
    • HBase
    • ZooKeeper
    • Kafka
  • Not managing offsets

Overview of Offset Management

Spark Streaming integration with Kafka allows users to read messages from a single Kafka topic or multiple Kafka topics.

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Blacklisting in Apache Spark

Categories: Hadoop Spark

At Cloudera, we’re always working to provide our customers and the Apache Spark community with the most robust, most reliable software possible. This article describes some recent engineering work on [SPARK-8425] that is available in CDH 5.10 and CDH5.11, as well as in upstream Apache Spark starting with the 2.2 release.

The work pertains to the Blacklist Tracker mechanism in Spark’s scheduler. This was the subject of a recent Spark Summit talk,

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Impala’s Next Step: Proposal to Join the Apache Software Foundation

Categories: Impala Kudu

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,

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Inside Santander’s Near Real-Time Data Ingest Architecture

Categories: Flume HBase Kafka

Learn about the near real-time data ingest architecture for transforming and enriching data streams using Apache Flume, Apache Kafka, and RocksDB at Santander UK.

Cloudera Professional Services has been working with Santander UK to build a near real-time (NRT) transactional analytics system on Apache Hadoop. The objective is to capture, transform, enrich, count, and store a transaction within a few seconds of a card purchase taking place. The system receives the bank’s retail customer card transactions and calculates the associated trend information aggregated by account holder and over a number of dimensions and taxonomies.

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What’s Next for Impala: More Reliability, Usability, and Performance at Even Greater Scale

Categories: Impala

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.

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