The Hortonworks Blog

Posts categorized by : Tez

Hortonworks Data Platform Version 2.2 represents yet another major step forward for Hadoop as the foundation of a Modern Data Architecture. This release incorporates the last six months of innovation and includes more than a hundred new features and closes thousands of issues across Apache Hadoop and its related projects.

Our approach at Hortonworks is to enable a Modern Data Architecture with YARN as the architectural center, supported by key capabilities required of an enterprise data platform — spanning Governance, Security and Operations.…

Apache Tez has been selected as a winner for 2014’s InfoWorld Bossie award. The “Bossies” identify the Best of Open Source software every year and are awarded by a panel of InfoWorld Test Center editors and industry expert reviewers. The Bossie awards celebrate game-changing open source software projects in different domains, and Apache Tez was selected in the Big Data Tools category.

Last year, Apache Hadoop with YARN as its architectural center was awarded a Bossie.…

Concurrent Inc. is a Hortonworks Technology Partner and recently announced that Cascading 3.0 now supports Apache Tez as an application runtime. Cascading is a powerful development framework for building enterprise data applications on Hadoop and is one of the most widely deployed technologies for data applications, with more than 175,000 user downloads a month. Used by thousands of businesses including eBay, Etsy, The Climate Corp and Twitter, Cascading is the de facto standard in data application development on Hadoop.…

The Apache Tez community is thrilled to announce the release of version 0.5 of the project. We’re referring to this as “the developer release” because it’s all about developers. The community focused on meeting the key needs of developers using Tez to create their applications and engines. Tez 0.5 includes clean and intuitive developer APIs, easy debugging, extensive documentation and deployment with rolling upgrades.

Apache Hadoop YARN paved the way for Apache Tez.…

Speed, Scale, and SQL Semantics

Since its inception and graduation as a Top Level Project (TPL) from Apache Foundation Project (ASF) in September 2010, Apache Hive has been steadily improving—in speed, scale, and SQL semantics—to meet enterprise requirements for both interactive and batch queries at Hadoop scale.

It has become a defacto standard for SQL queries over petabytes of data stored in Hadoop. It is a compliant SQL engine that offers familiarity to developers over a comprehensive and familiar set of SQL semantics for Apache Hadoop.…

This week we continue our YARN webinar series with detailed introduction and a developer overview of Apache Tez.  Designed to express fit-to-purpose data processing logic, Tez enables batch and interactive data processing applications spanning TB to PB scale datasets.  Tez offers a customizable execution architecture that allows developers to express complex computations as dataflow graphs and allows for dynamic performance optimizations based on real information about the data and the resources required to process it.…

Last week, Apache Tez graduated to become a top level project within the Apache Software Foundation (ASF). This represents a major step forward for the project and is representative of its momentum that has been built by a broad community of developers from not only Hortonworks but Cloudera, Facebook, LinkedIn, Microsoft, NASA JPL, Twitter, and Yahoo as well.

What is Apache Tez and why is it useful?

Apache™ Tez is an extensible framework for building YARN based, high performance batch and interactive data processing applications in Hadoop that need to handle TB to PB scale datasets.…

The Apache Pig community released Pig 0.13. earlier this month. Pig uses a simple scripting language to perform complex transformations on data stored in Apache Hadoop. The Pig community has been working diligently to prepare Pig to take advantage of the DAG processing capabilities in Apache Tez. We also improved usability and performance.

This blog post summarizes the progress we’ve made.

Support for Backends Other Than MapReduce

We made the Pig 0.13 architecture more general to support multiple backends beyond just MapReduce, while maintaining backward compatibility.…

This is the second in the series of blogs exploring how to write data-driven applications in Java using the Cascading SDK. The series are:

  • WordCount
  • Log Parsing
  • Historically, programming languages and software frameworks have evolved in a singular direction, with a singular purpose: to achieve simplicity, hide complexity, improve developer productivity, and make coding easier. And in the process, foster innovation to the degree we have seen today—and benefited from.

    Anyone among you is “young” enough to admit writing code in microcode and assembly language?…

    Introduced in 2008, Apache Hive has been the de-facto SQL solution in Hadoop. By 2012, SQL had become a key battleground for Hadoop and many vendors started to publish benchmarks showing massive performance advantages their solutions had over Hive. Each of these vendors predicted that Hive would eventually be supplanted by the proprietary solution they were pushing.

    The concerns about Hive’s performance were real. Hadoop in 2012 was a purely batch platform and no work had ever been done within Hive to address low-latency or interactive workloads.…

    On May 15, Owen O’Malley and Carter Shanklin hosted the second of our seven Discover HDP 2.1 webinars. Owen and Carter discussed the Stinger Initiative and the improvements to Apache Hive that are included in HDP 2.1:

    • Faster queries with Hive on Tez, vectorized query execution and a cost-based optimizer
    • New SQL semantics and datatypes
    • SQL-standard authorization
    • The Hive job visualizer in Apache Ambari
    • And many more

    Here is the complete recording of the webinar.…

    The first use of the term BoF session was used at the Digital Equipment Users’ Society (DECUS) conference in the 1960s. Its essence was to bring together like minds and thought leaders—just as birds of the feather flock together— to share and exchange computing ideas, in an informal yet spirited way. Since then, the organizers and sponsors of most computing conferences have been loyal to its essence and spirit.

    For ideas and innovation happen in collaboration—not in isolation. …

    The Apache Hive community has voted on and released version 0.13 today. This is a significant release that represents a major effort from over 70 members who worked diligently to close out over 1080 JIRA tickets.

    Hive 0.13 also delivers the third and final phase of the Stinger Initiative, a broad community based initiative to drive the future of Apache Hive, delivering 100x performance improvements at petabyte scale with familiar SQL semantics.…

    The power of a well-crafted speech is indisputable, for words matter—they inspire to act. And so is the power of a well-designed Software Development Kit (SDK), for high-level abstractions and logical constructs in a programming language matter—they simplify to write code.

    In 2007, when Chris Wensel, the author of Cascading Java API, was evaluating Hadoop, he had a couple of prescient insights. First, he observed that finding Java developers to write Enterprise Big Data applications in MapReduce will be difficult and convincing developers to write directly to the MapReduce API was a potential blocker.…

    We are excited to announce that the Apache™ Tez community voted to release version 0.4 of the software.

    Apache Tez is an alternative to MapReduce that provides a powerful framework for executing a complex topology of tasks for data access in Hadoop. Version 0.4 incorporates the feedback from extensive testing of Tez 0.3, released just last month.

    This release is especially meaningful because it coincides with completion of the Stinger Initiative (a collaborative community effort involving 145 developers across 44 companies) and the upcoming release of Apache Hive 0.13.…

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