Locking and latching are both key mechanisms employed by relational database management systems to ensure data integrity, consistency, and the serialization of resources. In the Db2 for z/OS IRLM manages the locks, but both Db2 and IRLM have internal latches.
Steve Thomas of CA Technologies presents a great introduction into the world of locks, latches, claims and drains. A must see for all developers working wit Db2 for z/OS as well as all DBAs wanting to refresh their knowledge.
There are a lot of practical SQLs for developer. We talk about pattern matching using regular expression, how to invoke external REST services using HTTPGETCLOB, and consuming the REST response in JSON and XML using the JSON or XML features in Db2 for z/OS.
The purpose of this article is to provide a couple of ways you can work with Spark and Db2 for z/OS while having your Apache Spark installation (standalone or cluster) working outside of z/OS and at the same time enabling a feature of Db2 for z/OS most people are not aware of.
The db2 logging process is an old strong process. You must take care of it because if all your active log data sets are not reusable because they are full, your db2 stops until it can offload them in archive logs. The performance of your recovery process is also strongly linked to your active log