Tag: Tuning

Feed: Planet big data. Author: Paul Johnson. In computing, massively parallel refers to the use of a large number of processors (or separate computers) to perform a set of coordinated computations in parallel (simultaneously). Source: Wikipedia. Teradata & MPP Beginnings Once upon a time, in a land far, far away…well, OK, California in the late 1970’s/early 1980’s to be precise…the MPP database world started to stir in earnest. Following on from research at Caltech and discussions with Citibank’s technology group, Teradata was incorporated in a garage in Brentwood, CA in 1979. Teradata’s eponymous flagship product was, and still is, a ... Read More

Feed: Databasejournal.com - Feature Database Articles. Author: . Oracle has provided access to its wait interface for several releases and with each new release it expands the range of wait information available, so much so that it's hard to not find something to examine. Of course, examination leads to investigation, which leads to tuning, even when there is nothing to tune. Such constant twiddling and tweaking is known as Compulsive Tuning Disorder, or CTD. Unfortunately, the more ways Oracle provides to interrogate the wait interface the more the DBA can fall victim to CTD. To help reduce the urge to ... Read More

Feed: Planet big data. Author: David Smith. Oksana Kutina and Stefan Feuerriegel fom University of Freiburg recently published an in-depth comparison of four R packages for deep learning. The packages reviewed were: MXNet: The R interface to the MXNet deep learning library. (The blog post refers to an older name for the package, MXNetR.) darch: An R package for deep architectures and restricted Boltzmann machines. deepnet: An R package implementing feed-forward neural networks, restricted Boltzmann machines, deep belief networks, and stacked autoencoders. h2o: The R interface to the H2O deep-learning framework. The blog post goes into detail about the capabilities of the packages, ... Read More

Feed: All Oracle Press Releases. Oracle today announced that Oracle Management Cloud is experiencing exceptional growth with nearly 950 new customers and partners across the globe within its first year of availability.  FORS, IDEA Cellular, and Safexpress are among the many organizations around the world choosing Oracle Management Cloud to help improve IT resource utilization, increase DevOps productivity, and ensure that critical applications are up and running. Part of the Oracle Cloud Platform, Oracle Management Cloud is a suite of next-generation integrated monitoring, management, and analytics cloud services that leverage machine learning and big data techniques against the full breadth ... Read More

Feed: Microsoft Azure Blog. Author: Marley Gray. Anatomy of a Smart Contract The concept of a Smart Contract has been around for awhile and is largely attributed to Nick Szabo’s work in the late 1990s. However, it remained an abstract concept until the summer of 2015 with the Frontier release of Ethereum as its first implementation. The promise of Smart Contracts is sprawling and has gotten the attention of every industry as a revolutionary disrupter that can change the way business is done forever. That remains to be seen, but like most first implementations of significantly important technology, there are ... Read More

Feed: Planet MySQL. Author: Jean-François Gagné. MySQL 5.7 introduced the LOGICAL_CLOCK type of multi-threaded slave (MTS).  When using this type of parallel replication (and when slave_parallel_workers is greater than zero), slaves use information from the binary logs (written by the master) to run transactions in parallel.  However, enabling parallel replication on slaves might not be enough to get a higher replication throughput (VividCortex blogged about such a situation recently in Solving MySQL Replication Lag with LOGICAL_CLOCK and Calibrated Delay).  To get a faster slave with parallel replication, some tuning is needed on the master. I already wrote/spoke many times about ... Read More

Feed: Planet MySQL. Author: MySQL High Availability. In this blog post, we will describe our Paxos-based solution, named eXtended COMmunications, or simply XCOM, which is a key component in the MySQL Group Replication. XCOM is responsible for disseminating transactions to MySQL instances that are members in a group and for managing their membership. Its key functionalities are: Ordered Delivery: Guarantees that messages (i.e. transactions) are delivered by the same order at all members Dynamic Membership: Provides functionalities to manage the set of MySQL Server instances belonging to the group Failure Detection: Along with Dynamic Membership, decides upon the fate of failed ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Tuesday, January 17, 2017 By Martin Görner and Robert Kubis, Google Cloud Developer Advocates With this new codelab and public data, discover what you can do with just a couple of lines of Java and Cloud Dataflow. The world is becoming more and more connected. Vast amounts of data are collected from sensors and systems to help with decision making in many areas. This data needs to be processed to extract analytical insights ... Read More

Feed: Big Data Feed. Author: itsing. Real-world case study in the telecom industryDebugging a real-life distributed application can be a pretty daunting task. Most common Google searches don't turn out to be very useful, at least at first. In this blog post, I will give a fairly detailed account of how we managed to accelerate by almost 10x an Apache Kafka/Spark Streaming/Apache Ignite application and turn a development prototype into a useful, stable streaming application that eventually exceeded the performance goals set for the application.The lessons learned here are fairly general and extend easily to similar systems using MapR Streams ... Read More

Feed: Databasejournal.com - Feature Database Articles. Author: . Your big data application needs regular extracts from your production systems. While many best practices exist for big data extract, transform and load (ETL) processes, we sometimes forget that these data-intensive procedures can affect the operational environment’s performance. Big Data Application Resource Usage Today’s big data applications are scaling up and out. This involves adding more CPU power, more memory, and more system resources. IT staff are also upgrading the hybrid hardware and software appliances used for big data information storage and execution of business analytics. As big data applications grow, they ... Read More