Category: Polybase

Feed: James Serra's Blog. Author: James Serra. Data virtualization goes by a lot of different names: logical data warehouse, data federation, virtual database, and decentralized data warehouse.  Data virtualization allows you to integrate data from various sources, keeping the data in-place, so that you can generate reports and dashboards to create business value from the data.  It is an alternative to building a data warehouse, where you collect data from various sources and store a copy of the data in a new data store. The main advantage of data virtualization is speed-to-market, where we can build a solution in a ... Read More

Feed: Henk's tech blog. Author: Henk. With the release of CTP3 SQL Server 2016 and its native In-database support for the open source R language you can now call both R, RevoScaleR functions and scripts directly from within a SQL query and benefit from multi-threaded and multi-core in-DB computations. Yet another SQLServer milestone! The R integration brings a lot of benefits and new scenarios to your end users; it brings the utility of data science to your applications without the need to ‘export’ the data to your R environment! Installing & Enabling SQLR integration To get started you will need ... Read More

Feed: James Serra's Blog. Author: James Serra. With so many product options to choose from for building a big data solution in the cloud, such as SQL Data Warehouse (SQL DW), Azure Analysis Services (AAS), SQL Database (SQL DB), and Azure Data Lake (ADL), there are various combinations of using the products, each with pros/cons along with differences in cost.  With many customers looking at using SQL DW, I wanted to mention various reference architectures that I have seen, ordered by most cost to lowest cost: Do staging, data refinement and reporting all from SQL DW.  You can scale compute power ... Read More

Feed: James Serra's Blog. Author: James Serra. Azure Data Lake Analytics (ADLA) is a distributed analytics service built on Apache YARN that allows developers to be productive immediately on big data.  This is accomplished by submitting a job to the service where the service will automatically run it in parallel in the cloud and scale to process data of any size.  Scaling is achieved by simply moving a slider, being careful to make sure the data and job is large and complex enough to provide parallelism so you don’t overprovision and pay too much.  When the job completes, it winds down ... Read More

Feed: James Serra's Blog. Author: James Serra. I previously talked about PolyBase and its enhancements (see PASS Summit Announcements: PolyBase enhancements).  There is some confusion on PolyBase use cases as they are different depending on whether you are using PolyBase with Azure SQL Data Warehouse (SQL DW) or SQL Server 2016, as well as the sources you are using it against.  The three main use cases for using PolyBase are: Loading data, federating querying, and aging out data.  Here is the support for those three uses cases in SQL DW and SQL Server 2016: PolyBase in: Parallelize Data Load (Blob and ... Read More

Feed: James Serra's Blog. Author: James Serra. Below I have attempted to list the various options for reporting off of Hadoop (HDInsight, HDP, Cloudera) using Power BI Desktop and Excel.  Some of the data sources prompt you to choose the Data Connectivity mode of either Import or DirectQuery.  For those that don’t you are limited to Import mode: Power BI via Microsoft Azure HDInsight Spark (Import or DirectQuery)  This is in Beta.  This works if HDInsight is using Blob storage or Azure Data Lake Storage (ADLS) Power BI via Microsoft Azure HDInsight (Import).  This works if HDInsight is connected to Blob ... Read More

Feed: James Serra's Blog. Author: James Serra. Microsoft’s end goal is for Azure to become the best cloud platform for customers to run their data workloads.  This means Microsoft will provide customers the best environment to run their big data/Hadoop as well as a place where Microsoft can offer services with our unique point-of-view.  Specific decision points on using Hadoop is if the customer wants to use open source technologies or not.  Some of the benefits of running open source software (OSS) on Azure include: Quick installs Support Easy scale Products work together Don’t need to get your own hardware ... Read More

Feed: James Serra's Blog. Author: James Serra. Microsoft has a new release for the Analytics Platform System (APS).  This appliance update is called APS 2016 and has been released to manufacturing and is now generally available.  APS is Microsoft’s scale-out Massively Parallel Processing fully integrated system for data warehouse specific workloads. This release is built on the latest SQL Server 2016 release, offers additional language surface coverage to aid in migrations from SQL Server and other platforms, adds PolyBase connectivity to the current versions of Hadoop from Hortonworks, additional PolyBase security with Kerberos support and credential support for Azure Storage ... Read More

Feed: James Serra's Blog. Author: James Serra. Microsoft usually has some interesting announcements at the PASS Summit, and this year was no exception.  I’m writing a set of blogs covering the major announcements.  Next up is the PolyBase enhancements. PolyBase is a technology that accesses and combines both non-relational and relational data, all from within SQL Server.  It allows you to run queries on external data in Hadoop or Azure blob storage.  The queries are optimized to push computation to Hadoop via MapReduce jobs. By simply using Transact-SQL (T-SQL) statements, you an import and export data back and forth between relational ... Read More

Feed: James Serra's Blog. Author: James Serra. Microsoft Connect(); is a developer event from Nov 16-18, where plenty of announcements are made.  Here is a summary of the data platform related announcements: Azure Data Lake Analytics is generally available in two datacenters in US (EMEA coming in Feb).  Azure Data Lake Analytics is a cloud analytics service that allows you to develop and run massively parallel data transformations and processing programs in U-SQL, R, Python and .Net over petabytes of data with just a few lines of code.  See Azure Data Lake Analytics now generally available Azure Data Lake Store is generally ... Read More