One of KSQL’s most powerful features is allowing users to build their own KSQL functions for processing real-time streams of data. These functions can be invoked on individual messages (user-defined functions or UDFs) or used to perform aggregations on groups of messages (user-defined aggregate functions or UDAFs).
The previous blog post How to Build a UDF and/or UDAF in KSQL 5.0 discussed some key steps for building and deploying a custom KSQL UDF/UDAF. Now with Confluent Platform 5.3.0, creating custom KSQL functions is even easier when you leverage Maven, a tool for building and managing dependencies in Java projects.
Read on to see just how easy it is.
Carrying out a customer survey, for example, can be useful to obtain crucial insights into the overall customer experience of your clients. But the data obtained from these surveys can be incredibly difficult to process, even after you’ve added all the results to a spreadsheet and especially if you receive a high volume of responses.
How do you process this information, then? Should you read the answers one by one? What if you want to know what people are saying about your brand on social media?
Click through for a demo.
This code is pretty simple and looks for an Azure SQL Server in each resource group, and then looks for the databases that aren’t master on each server. In this example I’m setting the storage account for Azure Threat Detection, but you could do anything you wanted in that last loop.
Click through for the script. Things like parallelism and error handling are exercises for the reader.
I was working with containers recently with Jenkins. I didn’t want the server process running on my machine all the time, but I did need to allow some communication. Jenkins uses 8080 by default, but agents need another port.
I figured there was a way to do this, and I found it on Stack Overflow, which is the perfect forum for a question like this. The answer?
You’ll need to click through for the answer.
Missing index request column order is pretty basic.
Instead, we’re gonna add these:
CREATE INDEX ix_spaces
ON dbo.Posts(ParentId, Score);
CREATE INDEX ix_tabs
ON dbo.Posts(Score, ParentId);
SQL Server is capable of using both intelligently. This is something I generally don’t like to do, but if you have queries which absolutely need differently-ordered index columns, it can make sense to do this. Just don’t expect SQL Server’s missing index DMV to tell you which order they should be in.
I made 2 unsuccessful attempts at running the SSIS Server Maintenance Job. However, after several hours of processing and still no available free space in the database, I knew the job wasn’t coping with the sheer number of rows it had to delete. The deletes all happen from the parent table (internal.operations) and then all child tables using using cascading deletes. This approach maintains referential integrity but is not great for performance.
Due to this, I needed a new approach to the maintenance of SSISDB. As we hadn’t maintained these tables for 13/14 months, I was asking too much of SQL Server to let me delete everything at once.
Read on for the solution.
Another key point is that even though SQL Server on Linux is supported on various distributions SQL Server can be installed on other distributions instead.
Although I would only advise this for testing purposes only because SQL Server would not be supported by Microsoft on these other distributions.
In reality, you can probably install SQL Server on more diverse distributions than the ones listed. However, I have focused on the main ones below.
As Kevin points out, there’s a difference between “working” and “supported.” If you’re futzing about with a dev database or trying to learn the platform, go ahead and install it on Elementary or some other unsupported distro. But if you have a production issue, the fact that you installed SQL Server on an ancient version of Slackware may win you plaudits but won’t get you support.
Snapshot isolation avoids most locking and blocking by using row versioning. When data is modified, the committed versions of affected rows are copied to tempdb and given version numbers. This operation is called copy on write and is used for all inserts, updates and deletes using this technique. When another session reads the same data, the committed version of the data as of the time the reading transaction began is returned.
By avoiding most locking, this approach can greatly increase concurrency at a lower cost than transactional isolation. Of course, “There ain’t no such thing as a free lunch!” and snapshot isolation has a hidden cost: increased usage of tempdb.
Gerald covers both varieties, Read Committed Snapshot Isolation and proper Snapshot Isolation. RCSI is definitely worth understanding in almost any environment, and even Snapshot Isolation has its uses.