Skip to main content

What is DB2 HADR?

DB2® High Availability Disaster Recovery (HADR) uses database logs to replicate data from the primary database to the standby database. 

Non-logged operations are allowed on the primary database, but not replicated to the standby database. If you want non-logged operations, such as updates to the history file, to be reflected in the standby database, you must take extra steps to cause this to happen.
The following are examples of cases in which operations on the primary database are not replicated to the standby database:

  • Tables created with the NOT LOGGED INITIALLY option specified are not replicated. Attempts to access such tables after an HADR standby database takes over as the primary database will result in an error.
  • All logged LOB columns are replicated. Non-logged LOB columns are not replicated. However, the space for them will be allocated on the standby database using binary zeroes as the value for the column.
  • Updates to database configuration using the UPDATE DATABASE CONFIGURATION and UPDATE DATABASE MANAGER CONFIGURATION commands are not replicated.
  • Database configuration and database manager configuration parameters are not replicated.
  • For user-defined functions (UDFs), changes to objects external to the database (such as related objects and library files) are not replicated. They will need to be setup on the standby via other means.
  • The recovery history file (db2rhist.asc), and changes to it, are not automatically shipped from the primary database to the standby database.
 It replicates data in real time from a primary database to one or more standby databases. In case the primary database fails, a standby database takes over as the new primary.


Labels:

Comments

Post a Comment

Popular posts from this blog

What is the difference between Elastic and Enterprise Redis w.r.t "Hybrid Query" capabilities

  We'll explore scenarios involving nested queries, aggregations, custom scoring, and hybrid queries that combine multiple search criteria. 1. Nested Queries ElasticSearch Example: ElasticSearch supports nested documents, which allows for querying on nested fields with complex conditions. Query: Find products where the product has a review with a rating of 5 and the review text contains "excellent". { "query": { "nested": { "path": "reviews", "query": { "bool": { "must": [ { "match": { "reviews.rating": 5 } }, { "match": { "reviews.text": "excellent" } } ] } } } } } Redis Limitation: Redis does not support nested documents natively. While you can store nested structures in JSON documents using the RedisJSON module, querying these nested structures with complex condi...
Post a Comment
Read more

Training LLM model requires more GPU RAM than storing same LLM

Storing an LLM model and training the same model both require memory, but the memory requirements for training are typically higher than just storing the model. Let's dive into the details: Memory Requirement for Storing the Model: When you store an LLM model, you need to save the weights of the model parameters. Each parameter is typically represented by a 32-bit float (4 bytes). The memory requirement for storing the model weights is calculated by multiplying the number of parameters by 4 bytes. For example, if you have a model with 1 billion parameters, the memory requirement for storing the model weights alone would be 4 GB (4 bytes * 1 billion parameters). Memory Requirement for Training: During the training process, additional components use GPU memory in addition to the model weights. These components include optimizer states, gradients, activations, and temporary variables needed by the training process. These components can require additional memory beyond just storing th...
Post a Comment
Read more

Error: could not find function "read.xlsx" while reading .xlsx file in R

Got this during the execution of following command in R > dat Error: could not find function "read.xlsx" Tried following command > install.packages("xlsx", dependencies = TRUE) Installing package into ‘C:/Users/amajumde/Documents/R/win-library/3.2’ (as ‘lib’ is unspecified) also installing the dependencies ‘rJava’, ‘xlsxjars’ trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.2/rJava_0.9-8.zip' Content type 'application/zip' length 766972 bytes (748 KB) downloaded 748 KB trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.2/xlsxjars_0.6.1.zip' Content type 'application/zip' length 9485170 bytes (9.0 MB) downloaded 9.0 MB trying URL 'https://cran.rstudio.com/bin/windows/contrib/3.2/xlsx_0.5.7.zip' Content type 'application/zip' length 400968 bytes (391 KB) downloaded 391 KB package ‘rJava’ successfully unpacked and MD5 sums checked package ‘xlsxjars’ successfully unpacked ...
Post a Comment
Read more