A Fine Slice Of SQL Server
Wolfgang Strasser points out a new feature with Azure Synapse Analytics:
Let’s call it by accident, that I found out that Azure Synapse Analytics now let’s you to link more than just one Power BI workspace.. There is an entry in the Release notes/Update menu that lists this option.
Read on to see what this means for you.
Comments closedEsat Erkec takes us through SET STATISTICS TIME ON:
The SET STATISTICS TIME ON statement returns a text report and this report includes how long it is taken by the query compilation and execution time of a query. To enable this option for any query we need to execute the SET STATISTICS TIME ON command before the execution of the query so that the execution time report will appear in the message of the query result panel until we turn off this option. All values of the report are shown in milliseconds type and its syntax like as below:
Read on to see how you can use it, as well as things to keep in mind as you do.
Comments closedGrant Fritchey answers a question:
While teaching about Extended Events and Execution Plans last week, Jason, one of the people in the class, asked: Is there a way in Extended Events to find queries using a Key Lookup operation? Sadly, the answer is no. However, you can query the Execution Plans in cache or in the Query Store to find this. Thanks for the question Jason. Here’s your answer.
Read on to see how.
Comments closedGlenn Berry reminds us that time flies:
SQL Server 2016 falls out of Mainstream Support on July 13, 2021. What this means is that there won’t be any new Service Packs or Cumulative Updates released for SQL Server 2016 after that date. It is still in Extended Support until July 14th, 2026. While in Extended Support, there will still be security and critical functional updates, if any are needed. This post is about SQL Server 2016 falling out of Mainstream Support.
Read on for more information about what this means, as it’s not a situation to panic and immediately change everything.
Comments closedApache Spark is a very popular analytics engine used for large-scale data processing. It is widely used for many big data applications and use cases. CDP Operational Database Experience Experience (COD) is a CDP Public Cloud service that lets you create and manage operational database instances and it is powered by Apache HBase and Apache Phoenix.
To know more about Apache Spark in CDP and CDP Operational Database Experience, see Apache Spark Overview and CDP Operational Database Experience Overview.
Apache Spark enables you to connect directly to databases that support JDBC. When integrating Apache Spark with Apache Phoenix in COD, you can leverage capabilities provided by Apache Phoenix to save and query data across multiple worker nodes, and use SELECT columns and pushdown predicates for filtering.
In this blog post, let us look at how you can read and write data to COD from Apache Spark. We are going to use an Operational Database COD instance and Apache Spark present in the Cloudera Data Engineering experience.
Read on for the process.
Comments closedSurya Sai Turaga and John O’Dwyer take us through change data capture in Delta Lake:
Change data capture (CDC) is a use case that we see many customers implement in Databricks – you can check out our previous deep dive on the topic here. Typically we see CDC used in an ingestion to analytics architecture called the medallion architecture. The medallion architecture that takes raw data landed from source systems and refines the data through bronze, silver and gold tables. CDC and the medallion architecture provide multiple benefits to users since only changed or added data needs to be processed. In addition, the different tables in the architecture allow different personas, such as Data Scientists and BI Analysts, to use the correct up-to-date data for their needs. We are happy to announce the exciting new Change Data Feed (CDF) feature in Delta Lake that makes this architecture simpler to implement and the MERGE operation and log versioning of Delta Lake possible!
Read on to gain an understanding of how it works.
Comments closedChris Webb shows how we can optimize the number of evaluation containers in Power BI:
Last week I showed how the new MaxEvaluationWorkingSetInMB registry setting could increase the performance of memory-hungry Power Query queries in Power BI Desktop. In this post I’ll show how the other new registry setting, ForegroundEvaluationContainerCount, can also help performance. Before I carry on I recommend you read the documentation on these new registry settings if you haven’t done so already.
To illustrate the effect of this setting I created ten identical Power Query queries feeding an Import mode dataset in a new .pbix file, each of which read data from the same 150MB CSV file, apply the a filter and then count the number of rows returned.
I don’t think I like having to modify a registry setting each time; that’s leading me to believe I should rarely (or never) mess with this.
Comments closedErik Darling found a way to do something interesting:
If you read the documentation for column store indexes, it says that column store indexes can’t be created on persisted computed columns.
And that’s true. If we step through this script, creating the column store index will fail.
But it turns out that if there’s a will, there’s a way. Even if this is something you shouldn’t wish to do because who knows what it will mess up.
Comments closedAdam Aspin takes us through creating Power BI themes:
Power BI has taken the world by storm when it comes to creating attention-grabbing dashboards that empower users. It has come to dominate the analytics arena with its ease of use, wide range of connectivity options, and the variety of available visuals. However, formatting (and reformatting) dashboard visuals can prove time-consuming and repetitive – as can standardizing the presentation of multiple dashboards to create a unified look and feel for a suite of reports. Most users would rather spend their time analyzing and delivering meaningful insights as opposed to applying colors and font choices to charts and tables. This article explains how Power BI themes can avoid that tedious work!
This is where the creation and application of Power BI themes comes in. A theme is a standardized definition of some – or all – of the formatting of a dashboard. This can range from defining a color palette and a selection of font choices to the detailed specification of each and every visual. Applying a theme allows you to format virtually every visual in a dashboard instantly. What is more, any changes that you subsequently make to a theme can be reapplied in a few clicks to update your dashboard’s presentation. Themes can be created once, then applied to dozens or even hundreds of Power BI dashboards to guarantee a coherent and rigorously standardized presentation style across a department or even an entire organization.
Read on to see some of the things you can do with customizing Power BI.
Comments closedJohn Mount has an update on a Python package:
The data algebra is a modern realization of elements of Codd’s 1969 relational model for data wrangling (see also Codd’s 12 rules).
The idea is: most data manipulation tasks can usefully be broken down into a small number of fundamental data transforms plus composition. In Codd’s initial writeup, composition was expressed using standard mathematical operator notation. For “modern” realizations one wants to use a composition notation that is natural for the language you are working in. For Python the natural composition notation is method dispatch.
Click through to see how it works and what’s new in the latest version.
Comments closed