The mappings Elastic SQL uses are:
Index = Table
Document = Row
Field = Column
This mapping is quite intuitive. Types are left out because they are obsolete in Elastic 6.0 on.
So let’s give it a try. I used the latest Elastic 6.4 for this demonstration and ran the queries from Kibana, although they can be run with curl or just a browser as well. First we will need some data. I found this article in Elastic documentation that suggests several data files ready to be loaded. I did not need all of the data so I only used the json file that contains all the works of William Shakespeare that can be downloaded here.
Feasel’s Law continues.
My colleagues send an message with a link that points to a script located on a shared drive to help our users reinstall their software.
Our users just click on the link in their Outlook and got a message saying:
\\servername.fqdn\share\softwarename\install.ps1 cannot be loaded because running scripts is disabled on this system. For more information, see about_Execution_Policies at https:/go.microsoft.com/fwlink/?LinkID=135170.
Users use Outlook that is a 32-bit process. If they click on link that points to a script, it will spawn a 32-bit console and run a 32-bit powershell.exe child process.
It appears that the ExecutionPolicy isn’t defined in the 32-bit PowerShell and set to its default value: “Restricted” although it’s defined in the 64-bit Powershell.
Read on for the solution to this issue as well as a second, similar issue.
Now, how can we send notifications from SQL Server in an easier way than using custom code or a Slack incoming webhook? Is there any integration or a Slack app? Yes. And guess what? I think you’ll like it because you don’t need to write a single line of code, and you don’t need to choose between CLR, PowerShell or any other language. It’s ironic, but the integration is called “Email”.
Speaking of CLR, I’ve had success with the SqlServerSlackAPI in the past.
In the previous part of this series, we have seen what a cluster shared volume is and what are the advantages and other considerations to keep in mind when deploying CSVs for SQL Server workloads. In this article, I will walk though actual installation of a failover cluster Instance leveraging CSVs.
To begin with, I will walk you through my cluster setup from 20,000 foot view. I created two brand new VMs running windows server 2012 R2 and renamed them accordingly. Nothing special w.r.t disk drives at this point, Just basic VMs with a system drive(C$).
The rest of the story is over at SQLShack.
What is DAX Guide? DAX Guide is a website offering a complete reference to the DAX language. Every function is presented with its complete syntax, a short description, and links to related functions and articles.
Is DAX Guide a tutorial to learn DAX?No, DAX Guide is not designed as a learning tool. The goal of DAX Guide is to provide a quick reference with accurate information. The only commitment is “quality first”.
What are some unique features of DAX Guide?DAX Guide is updated automatically through the monitoring of new versions of Microsoft products. Every DAX function comes with a compatibility matrix describing in which Microsoft products and versions the function may be available. Additional attributes highlight which functions perform a context transition, which arguments are executed within a row context, and which functions are obsolete or deprecated – in our opinion.
If that sounds interesting to you, check it out.
When we talk about Echarts, we will usually compare it with Highcharts. The relationship between them is a bit like the relationship between WPS and Office.
Highcharts is also a visualization library which you have to pay for it if you are going to use it. It has many advantages, for example, its documents and tutorials, JS scripts, and CSS are very detailed. It saves time and allows you to pay more attention to learning and developing. What’s more, it is very stable.
There are some good tools on this list.
In the past we used ETL techniques purely within the data-warehousing and analytic space. But, if one considers why and what ETL is doing, it is actually a lot more applicable as a broader concept.
- Extract: Data is available from a source system
- Transform: We want to filter, cleanse or otherwise enrich this source data
- Load: Make the data available to another application
There are two key concepts here:
- Data is created by an application, and we want it to be available to other applications
- We often want to process the data (for example, cleanse and apply business logic to it) before it is used
Thinking about many applications being built nowadays, particularly in the microservices and event-driven space, we recognize that what they do is take data from one or more systems, manipulate it and then pass it on to another application or system. For example, a fraud detection service will take data from merchant transactions, apply a fraud detection model and write the results to a store such as Elasticsearch for review by an expert. Can you spot the similarity to the above outline? Is this a microservice or ETL process?
Things like this are reason #1 why I expect data platform jobs (administrator and developer) to be around decades from now. The set of tools expand, but the nature of the job remains similar.
When we talk about Disaster Recovery or DR, it’s often coupled with the term High Availability or HA. Here are some definitions from my graduate course on HADR.
- Deals with minor outages, and failover solutions are automated
- The goal is to restore full system functionality in a short time
- Deals with major outages such as natural and man-made disasters
- Focuses on manual processes and procedures to restore systems back to their original state
- Characterized by a phased approach to restoring the primary site
In the context of SQL Server, HA would be Availability Groups (AG), Failover Clustering (FCI), Log Shipping and more. I won’t be addressing High Availability in this post, however.
Chrissy has a demo of everything in action, including running a series of tests to ensure that your DR site actually has everything.
At least since I started working on the SQL Server team (just after 7.0 shipped) and since then there have only been two VLF status codes:
- 0 = the VLF is not active (i.e. it can be (re)activated and overwritten)
- (1 = not used and no-one seems to remember what it used to mean)
- 2 = the VLF is active because at least one log record in it is ‘required’ by SQL Server for some reason (e.g. hasn’t been backed up by a log backup or scanned by replication)
A few weeks ago I learned about a new VLF status code that was added back in SQL Server 2012 but hasn’t come to light until recently (at least I’ve never encountered it in the wild). I went back-and-forth with a friend from Microsoft (Sean Gallardy, a PFE and MCM down in Tampa) who was able to dig around in the code to figure out when it’s used.
Read on to uncover the mysteries of the VLF status of 4.
After a little bit more research, I discovered that the return type for JSON_VALUE is limited to 4000 characters. Since JSON_VALUE is in lax mode by default, if the output has more than 4000 characters, it fails silently.
To force an error in future code I could use SELECT JSON_VALUE(@json, ‘strict $.FiveThousandAs’) so at least I would be notified immediately of an problem with my query/data (via failure).
Although strict mode will notify me of issues sooner, it still doesn’t help me extract all of the data from my JSON property.
Read on for the answer.