A Fine Slice Of SQL Server
One of the things that is lacking in the community is for some simple dump analysis for SQL Server, well no longer!
Introducing the Beta version of SQL Dump Analysis… sure it’s not super pretty, sure it’s not 100% yet… but it’ll give you the basic goods and get you on your way.
This is a website you upload SQL dumps to, rather than an executable you’d download. Still, check it out.
Comments closedPostgreSQL, by default, is configured to run everywhere with minimum resource utilization. To achieve maximum performance under specific scenarios, PostgreSQL’s parameters can be tuned to enhance performance. One such parameter that can impact performance in PostgreSQL is work_mem.
In this blog we will discuss how work_mem can be used to optimize performance in PostgreSQL.
Click through for that discussion.
Comments closedStithi Panigrahi does some troubleshooting:
Due to the potential impact on performance and storage costs, Azure Databricks clusters don’t capture networking logs by default. Follow the below instructions if you need to capture tcpdump to investigate multiple networking issues related to the cluster. These steps will capture a TCP dump on each cluster node–both driver and workers during the entire lifetime of the cluster.
Click through for an initiation script, which generates the actual script, which itself generates the TCP dumps.
Comments closedJosephine Bush builds on prior work:
Yes, you still need to do some work to maintain indexes in Azure SQL Database. This post will walk you through setting up statistic updates and index maintenance using Terraform.
Thanks to Tracy Boggiano for her directions for setting up the runbooks. If you want to do this manually instead of with Terraform, Tracy’s post walks you through it step by step. I only modified the role assignment so it had read to the entire subscription level to loop through every DB in the subscription.
Thanks to Kendra for blogging about index maintenance in Azure SQL. Her post helped me decide on index maintenance thresholds.
Click through for a link to Josephine’s GitHub repo and a walkthrough of how it all works.
Comments closedOlivier Van Steenlandt performs a hostile takeover:
The end user can save a Power BI report created in the Power BI Service in their own Personal Workspace but then they have no way to share it with their team. It remains a personal report/analysis.
When executing the analysis in Excel, they can distribute the Excel-file as they see fit.
The pitfall of personal workspaces in Power BI, from my point of view, is that if someone leaves the company, there isn’t a straight forward way for other end users to take-over previously created analysis.
This is where the Power BI Administrator can be of importance.
Read on to see how a Power BI Administrator can gain access to a personal workspace and migrate reports out of it.
Comments closedThamires Lemes digs into high transaction log utilization:
The transaction log in SQL Server records all changes made to a database, allowing for data recovery and consistency. When a transaction is initiated, it acquires space in the transaction log to record its activities. Long running transactions have the potential to hold the transaction log, and, depending on database write activity, cause errors and disruptions in the SQL Server environment.
It is important to point out that the transaction that is holding the transaction log might not be performing any write activities to consume additional log space, but subsequent transactions that writes to the transaction log will cause its utilization to increase, even if they are fast. The log space won’t be released until the oldest transaction concludes its execution.
Click through for a few queries on the topic. I’d also highly recommend sp_whoisactive for this kind of work.
Comments closedThe Big Data in Real World team pulls the plug on an application:
Apache Spark is a powerful open-source distributed computing system used for big data processing. However, sometimes you may need to kill a running Spark application for various reasons, such as if the application is stuck, consuming too many resources, or taking too long to complete. In this post, we will discuss how to kill a running Spark application.
Click through to see how you can do this.
Comments closedSemab Tariq shows off a tool for Postgres:
PgBouncer is a lightweight yet powerful connection pooling tool for PostgreSQL. It efficiently manages and reuses database connections, reducing the load on the server and improving performance. It acts as an intermediary between applications and the PostgreSQL database, optimizing connection usage and enhancing scalability.
This is a bit different from SQL Server, where connection pooling is built in. Read on to see how it works.
Comments closedDavid Fitzjarrell tackles a pair of errors:
One of the few errors taht strikes fear in the heart of a DBA is the dreaded:
ORA-01555 snapshot too old
and
ORA-22924 snapshot too oldOf course there are plenty of blogs instructing the DBA to simply “increase the undo_retention”, and there are cases where this works as expected. However, LOBs can be different as two different mechanisms exist for undo management. A LOB column can be configured to use retention to manage before mages of the data, but that can be confusing as each LOB column MAY have its own retention setting. The DBA_LOBS view reports whether LOG column uses retention or pctversion to manage undo, and the associated setting being used. Let’s -dig into this a bit deeper.
Read on to learn more about how LOB retention works, the types of issues you can run into with it, and how to correct those issues.
Comments closedHemantgiri Goswami takes a look at auto-growth:
Auto Growth is a feature that allows database files (primary, secondary, and log) to expand when the database file becomes full – without manual intervention.
Auto Growth feature is handy when we do not want to increase the size of database files manually. There are two ways you can set auto growth – using SQL Server Management Studio (SSMS hereafter) and T-SQL. Auto Growth can be configured – In Percent and Megabytes.
Auto-growth isn’t a problem on its own, though growth sizes, especially in older versions of SQL Server, were far too low for medium- and large-sized databases.
I don’t particularly like the 2.5 MB example Hemantgiri shows. I have a quick rule of thumb which is 64MB for small databases, 256-512 for medium-sized databases, and 1GB for large databases (assuming my underlying disk is fast). This limits the number of auto-growth events and, for log files in particular, keeps virtual log file counts more reasonable.
Comments closed