A Fine Slice Of SQL Server
Grant Fritchey starts us off slowly with containers:
The first command you have to learn is ‘docker pull’. You then have to supply something for it to pull, an image that will be used to create your containers. I’m using Powershell for the commands I’m posting this week. Here’s how you get an image with SQL Server 2017:
docker pull mcr.microsoft.com/mssql/server:2017-latest
Click through to learn more.
Comments closedErik Darling gives us a Sophie’s Choice:
It could have chosen a Hash Join, but then the order of the Id column from the Posts table wouldn’t have been preserved on the other side.
Merge Joins are order preserving, Hash Joins aren’t. If we use a Hash Join, we’re looking at ordering the results of the join after it’s done.
But why?
Read on to learn why, as well as why a few other things are so.
Comments closedMethod 2 : Use xp_cmdshell – although this does mean enabling xp_cmdshell , which is in many organisations as security violation
exec master..xp_cmdshell 'systeminfo'
Click through for several less controversial methods.
Comments closedDave Bland shows how to set up and read an extended event file on Azure SQL Database:
This first step when using T-SQL to read Extended Files that are stored in an Azure Storage Account is to create a database credential. Of course the credential will provide essential security information to connect to the Azure Storage Account. This first data point you will need is the URL to a blog storage container in you storage account. If you look below, you can see where you would place your storage account name and the blob storage container name.
Dave gives us the grand tour of the configuration process, including where things differ between on-prem SQL Server and Azure SQL Database (which is quite a bit)
Comments closedLandon Robinson shows how to override a Spark dependency located on the classpath:
This doesn’t draw the line exactly where the method changed from private to public, but generally speaking:
– gson-2.2.4.jar: the method is private, and therefore too old for use here
– gson-2.6.1: the method is public, and works fine.
– Somewhere between the two, the method’s status changed.So, because I had some functionality that required the method be public and accessible, it was important I specify the right version in my dependency manager (SBT). “That’s easy,” I thought. “No problem.”
Spoilers: there was a problem.
Comments closedRenu Tewari describes what MirrorMaker does for Kafka today and what is coming with version 2:
Apache Kafka has become an essential component of enterprise data pipelines and is used for tracking clickstream event data, collecting logs, gathering metrics, and being the enterprise data bus in a microservices based architectures. Kafka is essentially a highly available and highly scalable distributed log of all the messages flowing in an enterprise data pipeline. Kafka supports internal replication to support data availability within a cluster. However, enterprises require that the data availability and durability guarantees span entire cluster and site failures.
The solution, thus far, in the Apache Kafka community was to use MirrorMaker, an external utility, that helped replicate the data between two Kafka clusters within or across data centers. MirrorMaker is essentially a Kafka high-level consumer and producer pair, efficiently moving data from the source cluster to the destination cluster and not offering much else. The initial use case that MirrorMaker was designed for was to move data from clusters to an aggregate cluster within a data center or to another data center to feed batch or streaming analytics pipelines. Enterprises have a much broader set of use cases and requirements on replication guarantees.
Read on for the list of benefits and upcoming features.
Comments closedDmitry Tolpeko shows how you can collate Hadoop metrics from several ElasticMapReduce clusters:
The first step is to dynamically get the list of clusters and their IPs. Hadoop clusters are often reprovisioned, added and terminated, so you cannot use the static list and addresses. In case of Amazon EMR, you can use the following Linux shell command to get the list of active clusters:
aws emr list-clusters --activeFrom its output you can get the cluster IDs and names. As a cluster ID and IP can change over time, its name is usually permanent (like
DEVorAdhoc-Analyticscluster) so it can be useful for various aggregation reports.
Read on to see what you can do with this list of clusters.
Comments closedAdrian Buckman takes us through recent changes in Undercover Inspector:
#119 When the backups check module reports backup issues for a database but the issue is with a FULL or DIFF and the LOG is ok, we now show just the primary server in the Preferred replicas column as a FULL and DIFF only applies to the Primary – this reduces the number of warnings raised within the report as it will no longer report for all replica nodes if the AG backup preference is set to Prefer secondary or Secondary Only. See Git issue for more details.
Click through for the full change set.
Comments closedSamir Behara takes us through a few fallacies with distributed computing:
The network is reliable
Service calls made over the network might fail. There can be congestion in network or power failure impacting your systems. The request might reach the destination service but it might fail to send the response back to the primary service. The data might get corrupted or lost during transmission over the wire. While architecting distributed cloud applications, you should assume that these type of network failures will happen and design your applications for resiliency.To handle this scenario, you should implement automatic retries in your code when such a network error occurs. Say one of your services is not able to establish a connection because of a network issue, you can implement retry logic to automatically re-establish the connection.
There are some very good points in here.
Comments closedPamela Mooney shows how you can find three-part or four-part naming on a SQL Server instance:
The script below searches the metadata for views, sprocs and functions for occurrences of 3 and 4 part names. Three-part names consist of databasename.schemaname.objectname, and four-part names consist of servername.databasename.schemaname.objectname. Because the code searches metadata, it isn’t always perfect. If your comments mention a servername followed by a period, for example, it will be caught. Nevertheless, it’s a great place to begin looking, and a real help in getting rid of problems before they really bite you.
Click through for the script.
Comments closed