Tag: Cassandra

Feed: Planet MySQL; Author: Michael McLaughlin; Encountered a problem while running the RODBC library from the R prompt as the root user, as follows: > install.packages('RODBC') It failed with the following library dependency: checking for unistd.h... yes checking sql.h usability... no checking sql.h presence... no checking for sql.h... no checking sqlext.h usability... no checking sqlext.h presence... no checking for sqlext.h... no configure: error: "ODBC headers sql.h and sqlext.h not found" ERROR: configuration failed for package ‘RODBC’ * removing ‘/usr/lib64/R/library/RODBC’   The downloaded source packages are in ‘/tmp/RtmpdT1gay/downloaded_packages’ Updating HTML index of packages in '.Library' Making 'packages.html' ... done Warning message: ... Read More

Feed: AWS Compute Blog. Author: Tara Van Unen. This post courtesy of Massimiliano Angelino, AWS Solutions ArchitectDifferent enterprise systems—ERP, CRM, BI, HR, etc.—need to exchange information but normally cannot do that natively because they are from different vendors. Enterprises have tried multiple ways to integrate heterogeneous systems, generally referred to as enterprise application integration (EAI). Modern EAI systems are based on a message-oriented middleware (MoM), also known as enterprise service bus (ESB). An ESB provides data communication via a message bus, on top of which it also provides components to orchestrate, route, translate, and monitor the data exchange. Communication with the ... Read More

Feed: Planet MySQL; Author: Marco; Well here we go another MySQL conference / Percona Live.Another huge and important event/milestone for the MySQL community.  But this time I will not be there. First time in many years I had to decline, drop my speech and say... "No I am so sorry, this time I cannot come". Was not an easy choice, not only because I am always excited to meet old colleagues, but also because PLSC is a great moment for brainstorming and to identify what could be good to push-on or to investigate better. Especially this year where we have ... Read More

Feed: Planet MySQL; Author: Michael McLaughlin; I’ve started building the new image for the database courses. This one needs to include Oracle, MySQL, Cassandra, Hive, and MongoDB databases; and include examples for C, C++, Java, Perl, PHP, Python, R programming languages. Installing R was a surprise when I saw how many packages there are for it. It’s a standard yum command from the repository, but it will install 256 packages. The command is: yum install -y R Once you install it, you simply start the R interpreter, which is part of the Comprehensive R Archive Network (CRAN). Any installation of ... Read More

Feed: Blog Post – Corporate – DataStax. Author: Robin Schumacher, SVP and Chief Product Officer. Each time we have a major release, I look back and think there’s no way our team can top it; that future releases will somehow be less than what just went out the door. But every time I’m proven wrong when our next release becomes GA, and there’s no better example of that than what we’re announcing today.   DataStax Enterprise (DSE) 6 represents a major win for our customers who require an always-on, distributed database to support their modern real-time (what we call ‘Right-Now’) ... Read More

Feed: Blog Post – Corporate – DataStax. Author: Kathryn Erickson, Director of Strategic Partnerships at DataStax. Let’s skip to the last page in this book. You can head over to DataStax Academy right now and take a guided tour of DataStax Enterprise 6 using Official DataStax Docker Images which are approved for non-production use. We started our Docker journey in 2014 and and began exploring orchestration technologies shortly thereafter. In the fall of 2015, we announced production support for customer-built Docker images and offered best-practice guidance for anyone integrating DataStax Enterprise (DSE) into Docker. Today we are making DataStax-built images ... Read More

Feed: Hazelcast Blog. Author: David Brimley. 2018 In-Memory Data Grids resurgent IMDG (In-Memory Data Grids) have been around for well over a decade now and sit in a product sector that slightly overlaps NoSQL functionality. IMDGs initially came to the market in the early nougties when web sessions needed to scale past one sticky web-server, these were the days of what was then known as Tangosol Coherence. Since then the main use case for IMDGs has become general in memory caching and compute, where the IMDG sits between a slower persistent store like an RDBMS/Mainframe (or even a NoSQL Database) ... Read More

Feed: Planet MySQL; Author: Yelp Engineering; Since Yelp introduced its real-time streaming data infrastructure, “Data Pipeline”, it has grown in scope and matured vastly. It now supports some of Yelp’s most critical business requirements in its mission to connect people with great local businesses. Today, it has expanded into a diverse ecosystem of connectors sourcing data from Kafka and MySQL, and sinking data into Cassandra, Elasticsearch, Kafka, MySQL, Redshift, and S3. To ensure that the whole ecosystem is functioning correctly, Yelp’s Data Pipeline infrastructure is continually growing its repertoire of reliability techniques such as write-ahead logging, two-phase commit, fuzz testing, ... Read More

Feed: Planet MySQL; Author: Mark Callaghan; I prefer to use Index Structures when writing about algorithms for indexing data stored on disk and SSD but Access Methods is another popular name. Recently I have been working on a high-level comparison (lots of hand waving) of index structures in terms of read, write, space and cache amplification.I started by dividing the index structures into tree-based and hash-based. Tree-based support range queries while hash-based do not. Most of my experience is with tree-based approaches. There was a lot of research on hash-based in the 80s (extendible, dynamic and linear hashing), they are ... Read More

Feed: Redis Labs. Author: Harish Doddi. Machine Learning is at the core of many modern systems today. Delivering more precise predictions and recommendations can make the difference between gaining or losing new customers and revenue. Delivering real-time predictions for mission-critical applications with low latency while also performing online learning, composite modeling and constant experimentation requires a powerful infrastructure. Building this pipeline on your own can be extremely challenging, but combining the Datatron and Redis Labs platforms simplifies powerful online learning and productionizing machine learning. Datatron Platform Data scientists use Datatron Enterprise to easily develop and manage Machine Learning (ML) and ... Read More