I have been assigned to move 10g database to AWS Oracle 12c. Size of data is around 20 GB of actual data but 900 GB has been allocated. So we will need to decrease that. Any suggestions on how to migrate and reduce the size of the database?
This is a good summary of several options:
Importing Data Into Oracle on Amazon RDS
Also here is the Oracle migration Whitepaper.
The solution depends on the size of your data and the accepted downtime.
Personally I used Data Dump in a project, it works well for the size of data you have. I'm not sure about the resizing.
Related
I'm creating AWS RDS instance to migrate existing on-prem oracle database to AWS Rds instance.
Existing On-prem oracle database is appox 700GB.
I've two queries
what allocate storage size should i use for RDS oracle database instance,
should it be equal or greater then on-prem oracle database?
which instance type should be suitable for size of database?
If you are using S3 import method with Data Pump, you would need sufficient space to download the backup file to RDS Oracle instance + restore the same, so a little more than double should be a good option to create with(~1.5TB). If you are using some other method where you don't need the backup file on RDS, you can try provisioning around 800 GB initially.
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Oracle.Procedural.Importing.html#Oracle.Procedural.Importing.DataPump
It depends on your workload, and you might need to look at current Oracle AWR reports to analyze suitable CPU and RAM requirements. Nevertheless, you can start with something which you feel should suffice, and scale up or down as needed.
I was wondering whether MySQL commands like NOLOCK or creation of indexes is actually supported on Aurora AWS? Also, can I do performance issue investigation or is Aurora AWS a "black-box" to me?
The Aurora it is completely different database than MySQL, but when it comes to the compability with MySQL or PostgreSQL Amazon team did a lot so that there would not be a lot of differences. "The Amazon Aurora MySQL is designed to be wire-compatible with MySQL 5.6 and 5.7 using the InnoDB storage engine. Certain MySQL features like the MyISAM storage engine are not available with Amazon Aurora." Amazon Aurora MySQL 2.01 does not currently also support the following MySQL 5.7 features:
Global transaction identifiers (GTIDs)
Group replication plugin
Increased page size
InnoDB buffer pool loading at startup
InnoDB full-text parser plugin
Multisource replication
Online buffer pool resizing
Password validation plugin
Query rewrite plugins
Replication filtering
The CREATE TABLESPACE SQL statement
X Protocol
(source:https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/AuroraMySQL.Updates.2022.html)
But it changes from release to release.
Answering to you question about a performance monitoring. You can monitor Aurora database from AWS Console or by using queries directly on Aurora database, the same as in case of MySQL. Staring from version 2.03 there is also available the performance schema.
UNLOCK command - I am not sure whether it also exists in native MySQL, but there is possiblity to set transaction isolation level.
Indexes - yes, you can also create indexes on Aurora.
I hope the information will be useful for you.
We have a production Oracle 11g SE1 database in an AWS RDS instance. Seems like the Oracle statpack user is using huge storage space from the total storage. I want to purge some statpack snapshots to free some space. Has purging those snapshots an effect to the data of the database? Or is there any other side effects?
I am trying to create a proof of concept showing that it is possible for a company to migrate their data from their oracle 12c DB to a hadoop system..
To do this I have started a Oracle Linux 7 instance on AWS. I am planning to install Oracle 12c on it.. after that I have to create dummy tables and send them to Hadoop..
can this be done? From my initial research I can see that Sqoop and Oracle GoldenGate can do that.. also if this goes live i would have to transfer billions of records from oracle 12c to HDFS..
Any help or advice is much much appreciated..
You must use sqoop for transform your oracle data to hive. You can read this for more info
We have an Oracle Database that resides tables. We would like to implement a new project as I mentioned in title; Oracle to Cassandra real-time replication.
But this new Cassandra environment would be as a reporting service. From the application (in-house), datas is inserted to Oracle production environment. Then our custom service (or what ever) will read delta and insert to Cassandra (this would be like Goldengate may be).
Briefly, does the Cassandra will answer our needs for this scenario?
In our case, we have 20 oracle DBs in different locations (these 20 dbs has similar implementation) 1 central report DB that is daily refresh from these 20 DBs. We use "outdated" snapshot technology, every night our central single report DB (REPORTDB) with fast refresh option, we gather the daily delta from these 20 dbs within oracle ss. we need a structure that reads data from 20 dbs and real-time injection to new cassandra database just like REPORDB
These days you can run spark jobs on Cassandra, thanks to Datastax so yes it can be used as a reporting tool. It's best utilized as a key value store if your number of writes are high compared to your reads.
Reading delta is not real time so you should try using Oracle's AQs. I've been doing real time replication of Oracle to Cassandra using Oracle's AQ and Apache Storm for almost 4 years now and it's running flawlessly.
I don't understand this Oracle/Cassandra architecture running alongside.
Either Oracle suits your needs then you should stick with it. Or it doesn't and you need scalability/high availability then switch to Cassandra.
Can you elaborate on the reasons that make you choose Cassandra for the reporting service ?