Apache Parquet, the open-source columnar storage format for Hadoop, recently graduated from the Apache Software Foundation Incubator and became a top-level project. Initially created by Cloudera and Twitter in 2012 to speed up analytical processing, Parquet is now openly available for Apache Spark, Apache Hive, Apache Pig, Impala, native MapReduce, and other key components of the Hadoop ecosystem.
During the last months Martin Fowler among others have claimed that a microservices architecture should always start with a monolith, but Stefan Tilkov is convinced this is wrong, building a well-structured monolith with cleanly separated modules that later may be pulled apart into microservices is extremely hard, if not impossible in most cases.
Latest version of MemSQL, in-memory database with support for transactions and analytics, includes a new Community Edition for free use by organizations. MemSQL 4, released last week, also supports integration with Apache Spark, Hadoop Distributed File System (HDFS), and Amazon S3.
NASA Center for Climate Simulation (NCCS) is using Apache Hadoop for high-performance data analytics. Glenn Tamkin from NASA team, recently spoke at ApacheCon Conference and shared the details of the platform they built for climate data analysis with Hadoop.
Big data vendors Hortonworks, IBM, and Pivotal recently announced that their Hadoop based platform products will use the common Open Data Platform (ODP). They made the announcement at the recent HadoopSummit Europe Conference of the open platform which includes Apache Hadoop 2.6 (HDFS, YARN, and MapReduce) and Apache Ambari software.
After three developer previews, six release candidates and over 1500 closed tickets the Apache foundation has announced version 1.0 of Apache HBase, a NoSQL database in the Hadoop ecosystem. After more than 7 years of active development, the team behind HBase felt that the project had matured and stabilized enough to warrant a 1.0 version.
A service is a logical construct owning a business capability and made up of internal autonomous components or microservices that together fulfil the responsibilities of the service, Jeppe Cramon suggests continuing a previous series of blog posts clarifying his view on building services around business capabilities and bounded contexts.
Matt Ranney, Chief Systems Architect at Uber, gave an overview of their dispatch system, responsible for matching Uber's drivers and riders. Ranney explained the driving forces that led to a rewrite of this system. He described the architectural principles that underpin it, several of the algorithms implemented and why Uber decided to design and implement their own RPC protocol.
The goal of software is to sustainably minimize lead time to positive business impact, everything else is detail, Dan North claimed in a presentation at the QCon London conference describing ways of reasoning about code and how this leads him into an architecture style that may fit microservices.
Pivotal recently released Spring XD 1.1 GA with new features including stream processing with Reactor, RxJava, Spark Streaming and Python. Additionally support for Kafka, batching and compression with RabbitMQ, and support for container group management when running on YARN are now featured.
The assumption that a large system must have a single environment, often with a one-to-one mapping between a project’s scope and the system built are challenged today Stefan Tilkov explains when looking into ways to split a large system into smaller parts and comparing the characteristics of systems, applications and microservices.
Google announced last week the release of open source MapReduce framework for C, called MR4C, that allows developers to run native code in Hadoop framework. MR4C framework brings together the performance and flexibility of natively developed algorithms with the scalability and throughput provided by Hadoop execution framework.
Pivotal has decided to open source core components of their Big Data Suite and has announced the Open Data Platform, an initiative promoting open source and standardization for Big Data.
Project Pachyderm Aims to Build "Modern" Hadoop using Docker and CoreOS.
An article by Jin Scott - A tale of two clusters: Mesos and YARN – describes hardware silos created by using different resource managers on different hardware clusters, most popular being Mesos and Yarn and introduces Myriad – a solution allowing to run a YARN cluster on Mesos.