SAP Sybase Blog

Challenge 1: Massive Data Growth

Massive amounts of data is being created every year and as per he IDC EMC report data growth would be 40K Exabytes by 2020 :

http://germany.emc.com/collateral/about/news/idc-emc-digital-universe-2011-infographic.pdf

http://www.emc.com/collateral/analyst-reports/idc-the-digital-universe-in-2020.pdf

Challenge 2: Fast access to business decision making information.

Business & People want fast exact and correct answer of all questions from this massive amount of data.

Challenge 3: Current Technologies Can not deliver with this massive data growth.

Historical DBMS :

Historically database systems were designed to perform well on computer systems with limited RAM, this had the effect that slow disk I/O was the main bottleneck in data throughput. Consequently the architecture of these systems was designed with a focus on optimizing disk access, e. g. by minimizing the number of disk blocks (or pages) to be read into main memory when processing a query.

New Hardware Architecture ( up to or more 128 Cores of CPU and 2TB of RAM)

Computer architecture has changed in recent years. Now multi-core CPUs (multiple CPUs on one chip or in one package) are standard, with fast communication between processor cores enabling parallel processing. Main memory is no-longer a limited resource, modern servers can have 1 TB of system memory and this allows complete databases to be held in RAM. Currently server processors have up to 80 cores, and 128 cores will soon be available. With the increasing number of cores, CPUs are able to process increased data per time interval. This shifts the performance bottleneck from disk I/O to the data transfer between CPU cache and main memory

Need of In-memory Technology SAP HANA :

From the discussion above it is clear that traditional databases might not use current hardware most efficiently and not able to fulfill current and future business need.

The SAP HANA database is a relational database that has been optimized to leverage state of the art hardware. It provides all of the SQL features of a standard relational database along with a feature rich set of analytical capabilities.

Using groundbreaking in-memory hardware and software, HANA can manage data at massive scale, analyze it at amazing speed, and give the business not only instant access to real time transactional information and analysis but also more flexibility. Flexibility to analyze new types of data in different ways, without creating custom data warehouses and data marts. Even the flexibility to build new applications which were not possible before.

HANA Database Features

Important database features of HANA include OLTP & OLAP capabilities, Extreme Performance, In-Memory , Massively Parallel Processing, Hybrid Database, Column Store, Row Store, Complex Event Processing, Calculation Engine, Compression, Virtual Views, Partitioning and No aggregates. HANA In-Memory Architecture includes the In-Memory Computing Engine and In-Memory Computing Studio for modeling and administration. All the properties need a detailed explanation followed by the SAP HANA Architecture.

Source : www,sap.com and emc and idc reports.

Always consider to migrate the Development environment first , then UAT. Before moving to production Perform Regression testing on UAT enviornment.

Please consider to create the script to perform update stats,xp_postload(drop and re create index) for each and every database.

Steps for an ASE Database( You can repeat same steps for other databases) :

Step 1: Run the consistency checks in ASE database in Source (AIX) environment, to make sure that everything is fine.

Step 2: Put the database in single user mode.

Step3: Make sure there is no user activity on the Source Database .

Step 4: Run the sp_flushstats in the database.

Step 5: Take the backup of the database in Source (AIX) environment.

Step 6: Ftp the Files to Target environment. (AIX to Linux)

Step 7: Create and build the dataserver and databases in target Linux environment with exactly same configuration.
You might require to change some of the config param in Linux environment for performance point of view. ( Lets not discuss it here, as it is out of context).

Step 8: Also migrate the Login, roles from source server to target server

Step 9: Load the database in Linux environment.
(If there were user activity during dump process, load will be fail.)

Step 10: Online the database. If the target ASE version is new with source, It will also perform upgrade in this step.

Step 11:  Fix the corrupt indexes using the xp_postload. If the Database size is more than 20G, try drop and re-create index , in this case xp_postload would not be effective.

Step 12: Update the stats on all tables.

Step 13:  If there is replication setup in your environment, please setup replication after that.

Issue Faced:

1. If there is any user online during backup process, your load will fail( in the step for cross platform conversion).

2. After online database, we seen the -ve values in sp_helpdb output for few databases. There are two ways to fix this :

i) Try to run dbcc

dbcc usedextents(<DB name or DB ID>, 0, 1, 1)

ii) Use the Traceflag  7408 and 7409 in Run Server file and reboot the instance. It will not take much time as compare first option.

Traceflag 7408 : Force the server to scan *log segment* allocation pages; to recalculate free log space rather than use saved counts at boot time.
Traceflag 7409 : Force the server to scan *data* segment allocation pages; to recalculate free data page space rather than use saved counts at boot time.

Please let me know if you are planning for migration and need any assistance.

Wait is over Now !! 

Please download the Complete ebook for SAP Sybase ASE Q&A Bank Version 1.0  as below:

Newest Features

For those who are familiar with earlier versions of Sybase IQ, here are the new features added to from SAP Sybase IQ 15.

• Performance enhancements: The column store engine has been enhanced with extreme compression capabilities that improve I/O rates and reduce the amount of data to be stored on disk.
• High-speed data loading: High-performance data loading ingests large amounts of data faster than ever — from terabytes to petabytes — making big data available to applications and people faster.
• Improved scalability: Key improvements maintain high performance and efficiency for the growing volume of unpredictable, user-driven analytic workloads.
• Data protection: Administrators have further options for protecting the security of enterprise systems.
• Heightened availability: Enhancements help ensure that enterprise data is always available to business-critical analytics and dashboards.

Guys,
Came across below Replication Server Questions, might help you for yours interview preparation. It also includes few ASE questions.
Also Updated the Interview Question Page.
Thanks,

1. What is the difference between MSA and Warm standby ?

2. How can we perform fail over in Case of Warm Stand by and MSA?

3. What will happen, if the queue has data in case of fail over to warm standby?

4. For standby point of view which one is better warm standby or MSA?

5. How can we sync the warm standby database ? If there is some data in queue, what will you do?

6. What is the config parameter you can use to tune a rep agent?

7. Suppose there are 20,000 trans which are getting fail and you need to skip all these trans using error class. Please let me know high level overview to setup
error class?

8. How the multiple replication server can improve the performance as compare to single replication server ?

9. Suppose the query is running slow , how will you investigate?

10. Suppose tempdb log segment is full, how will you troubleshoot?

11. Suppose for a very big database , backup takes 4 hrs to complete . During the backup, due to heavy activity from user log is full, after 2 hours ? What will you do now?

12. How can we guess, in how much time queue will be drain?

13. Suppose queue is getting full, what can be point of bottleneck and why?

14. Suppose log for a database is getting full, how will you trouble shoot? Why log increase is not a better idea? ( Server version is below 15.7)

15. How will you check the latency and what is the latency ?

16. Suppose you want to sync a table in a warm stand replication , How will you do?

17. What are the various factor which can effect rep agent performance?

18. How can you make sure rep agent is running fine ( means scanning is going well in Primary site)?

19. How can we see the number of commands in a transaction in queue?

20. Suppose you have 5000 locks at primary side , and your one delete statement ( which is effecting 7000 rows)went fine. Now in case of Replicate dataserver ( has same number of locks), you are getting out of lock situation? Why it was successful at primary side , what it did not go well in replicate side, despite of primary and replicate have same number of locks?

21. What are the situations when we require to drain the queues?

22. In unix , suppose one dba modifies some of files including dataserver binary to non sybase user, and you want to fix this situation asap? What you will do?

23. Suppose there is thread down issue in replication for target side, and you fetched that its down due to duplicate row? How can we make sure , is it due to duplicate row or duplicate key?

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