Tag: partitions

Feed: Featured Blog Posts - Data Science Central. Author: Packt Publishing. The diverse fields in which machine learning has proven its worth is nothing short of amazing. At the heart of machine learning are the various algorithms it employs to classify data and predict outcomes. This article highlights two greedy classifiers that, albeit simple, can be extremely powerful in their own right.   This article is an excerpt from the book Machine Learning with R, Third Edition, written by Brett Lantz. This book provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experience ... Read More

Feed: Planet PostgreSQL. On 2nd of April 2019, Alvaro Herrera committed patch: Report progress of CREATE INDEX operations     This uses the progress reporting infrastructure added by , adding support for CREATE INDEX and CREATE INDEX CONCURRENTLY.   There are two pieces to this: one is index-AM-agnostic, and the other is AM-specific. The latter is fairly elaborate for btrees, including reportage for parallel index builds and the separate phases that btree index creation uses; other index AMs, which are much simpler in their building procedures, have simplistic reporting only, but that seems sufficient, at least for non-concurrent builds.   ... Read More

Feed: Cloudera Engineering Blog. Author: Bikas Saha. Apache Spark is one of the most popular engines for distributed data processing on Big Data clusters. Spark jobs come in all shapes, sizes and cluster form factors. Ranging from 10’s to 1000’s of nodes and executors, seconds to hours or even days for job duration, megabytes to petabytes of data and simple data scans to complicated analytical workloads. Throw in a growing number of streaming workloads to huge body of batch and machine learning jobs — and we can see the significant amount of infrastructure expenditure on running Spark jobs. Costs that ... Read More

Feed: Planet MySQL; Author: Dave Stokes; I gave a thirty minute talk at Drupalcon this week on the features in MySQL 8.0 that would be of interest to developers and for such a short talk (and I cut slides to allow for audience questions) I could only cover the highlights. One attendee gently chastised me over no including their favorite new MySQL 8.0 feature -- functional indexes. What is a Functional Index? The manual says MySQL 8.0.13 and higher supports functional key parts that index expression values rather than column or column prefix values. Use of functional key parts enables indexing of ... Read More

Feed: Planet MySQL; Author: Frederic Descamps; Everywhere I go to present MySQL InnoDB Cluster, during the demo of creating a cluster, many people doesn’t understand why when I’ve 2 members, my cluster is not yet tolerant to any failure. Indeed when you create a MySQL InnoDB Cluster, as soon as you have added your second instance, you can see in the status: "status": "OK_NO_TOLERANCE", "statusText": "Cluster is NOT tolerant to any failures.", Quorum Why is that ? It’s because, to be part of primary partition (the partition that holds the service, the one having a Primary-Master in Single Primary Mode, ... Read More

Feed: Planet MySQL; Author: MySQL Server Dev Team; In MySQL, historically GROUP BY was used to provide sorting as well. If a query specified GROUP BY, the result was sorted as if ORDER BY was present in the query. mysql-5.7> CREATE TABLE t (id INTEGER, cnt INTEGER); Query OK, 0 rows affected (0.03 sec) mysql-5.7> INSERT INTO t VALUES (4,1),(3,2),(1,4),(2,2),(1,1),(1,5),(2,6),(2,1),(1,3),(3,4),(4,5),(3,6); Query OK, 12 rows affected (0.02 sec) Records: 12 Duplicates: 0 Warnings: 0 mysql-5.7> SELECT id, SUM(cnt) FROM t GROUP BY id; +------+----------+ | id | SUM(cnt) | +------+----------+ | 1 | 13 | | 2 | 9 | | ... Read More

Feed: Blog – Hazelcast. Author: David Brimley. We are pleased to announce the production-ready release of Hazelcast IMDG 3.12. We’ve crushed a lot of bugs, provided general performance improvements, plus we’ve added some great new features (more of which below). The release by numbers: 676 Issues 784 Pull Requests 47 Committers 168 Days Elapsed CP Subsystem The new CP Subsystem provides implementations of Hazelcast’s existing concurrency APIs (locks, atomics, semaphores, latches) using a system based on the Raft Consensus Algorithm. Correct operation of concurrent data structures is a must, especially during network failures. This new feature provides a level of ... Read More

Feed: Planet MySQL; Author: HowToForge; This tutorial shows the installation of ISPConfig 3.1 on a CentOS 7.6 (64Bit) server. ISPConfig is a web hosting control panel that allows you to configure the following services through a web browser: Apache web server, PHP 7.2, Postfix mail server, MySQL, BIND nameserver, PureFTPd, SpamAssassin, ClamAV, Mailman, and many more. 1 Requirements To install such a system you will need the following: A Centos 7.6 minimal server system. This can be a server installed from scratch as described in our Centos 7 minimal server tutorial or a virtual-server or root-server from a hosting company that ... Read More

Feed: AWS Big Data Blog. In the world of big data, a common use case is performing extract, transform (ET) and data analytics on huge amounts of data from a variety of data sources. Often, you then analyze the data to get insights. One of the most popular cloud-based solutions to process such vast amounts of data is Amazon EMR.Amazon EMR is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS. Amazon EMR enables organizations to spin up a cluster with multiple instances in a matter of few minutes. It also ... Read More

Feed: Microsoft Azure Blog. Author: Parul Matah. This is a three-part blog post series about how organizations are using Azure Cosmos DB to meet real world needs, and the difference it’s making to them. In part 1, we explored the challenges Skype faced that led them to take action. In part 2, we examined how Skype implemented Azure Cosmos DB to modernize its backend infrastructure. In this post (part 3 of 3), we cover the outcomes resulting from those efforts. Note: Comments in italics/parenthesis are the author's. The outcomes Improved throughout, latency, scalability, and more Using Azure Cosmos DB, Skype ... Read More