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Posts Tagged ‘sybaseblog’

dbcc checkdb vs dbcc checkstorage

June 25th, 2012 No comments

Checkstorage will detect allocation errors, it is a reasonable substitute for dbcc checkalloc (checkstorage will report a fair number of issues that checkalloc will not, many of them trivial things, and checkalloc may be able to detect a few odd conditions
checkstorage does not.

What checkstorage won’t catch are issues with index tree (keys out of order, index entries that point to missing rows, rows
that are not indexed).  So checkstorage is not a good substitute for checkdb.

Source :www & sybooks.

Performance Issue

June 24th, 2012 No comments

Few days back I have faced performance issue in one of our prod data server. I would like to share here.

User was running batch for pushing 90000 rows in a database and batch was not moved from last 1.5 hrs.

On login in the server I found response of the server was not good, it was taking more time to execute a simple query as usual. In first glance, it was looking like user job is hogging the resources, as user job spid was in syslogshold and not moved from long time.

We do some analysis and finally found the cpu usage for server was 100%. ( I used sp_monitor). I concluded that this high cpu usage is slowing down the server performance.

The next task was finding the query which was taking more cpu time. As server was on 15 version, I ran the below sql querry for mon tables for getting the high cpu usage.

select top 10  s.SPID, s.CpuTime, t.LineNumber, t.SQLText from master..monProcessStatement s, master..monProcessSQLText t where s.SPID = t.SPID order by s.CpuTime DESC

http://sybaseblog.com/sybasewiki/index.php?title=Query_-_Which_currently_executing_queries_are_consuming_the_most_CPU_%3F

We asked application team to check the reported spid and if possible, please abort the tran. There was select queries which were  taking maximum cpu . As they requested us to kill, we aborted/killed from data server.

After few seconds, data server cpu started fluctuating from 50 to 100% and finally it was below 50%.

Application batch of 10K inserts moved very quickly and finally issue resolved.

You can get full details on MDA queries @ http://sybaseblog.com/sybasewiki/index.php?title=Category:MDA_Table_Query

Thanks.

Sybase ASE Database: Cost Considerations and Advantages

June 22nd, 2012 No comments

Recently SAP contracted with IDC to conduct a study of relational database management (RDBMS) users to determine the cost factors encountered by those users in running a relational database, and the extent to which (if any) Sybase ASE could save users money in running their systems. IDC recruited 12 organizations that were willing to let us examine deeply their costs in running both Sybase ASE and other RDBMS products.

IDC asked a number of detailed questions regarding the organizations’ use of database software, their staffing costs, their hardware costs, and their software license and maintenance costs. IDC then analyzed the data using a well-established five-year model for calculating total cost of ownership (TCO), and came to some compelling conclusions.

Read More : http://blogs.sap.com/sme/2012/06/21/sybase-ase-database-cost-considerations-and-advantages/#comment-3116

Categories: ASE, News Tags: , , , ,

SAP Becomes Fastest-Growing Vendor in Relational Database Market

June 8th, 2012 No comments

WALLDORF, Germany, June 7, 2012 /PRNewswire/ — SAP AG (NYSE: SAP) today announced it is the fastest-growing among the top vendors in the relational database management systems (RDBMS) market, according to a new report(1) from IDC.

 

Source & Complete  Report @http://www.itnewsonline.com

Categories: ASE, Database, News, SAP, Start Sybase Tags: , , ,

SAP Unveils Unified Strategy for Real-Time Data Management to Grow Database Market Leadership!!!

April 10th, 2012 No comments

Finally the curtain is up :

SAP today provided the following road map details and areas of strategic innovation and investment of its database portfolio to increase its database market leadership by 2015:

  • SAP HANA platform: This state-of-the-art in-memory platform is planned to be the core of the SAP real-time data platform, offering extreme performance and innovation for next-generation applications.
  • SAP Sybase ASE: SAP Sybase ASE is intended as a supported option for SAP Business Suite applications while SAP HANA is planned to augment the extreme transactions of SAP Sybase ASE with real-time reporting capabilities.
  • SAP® Sybase IQ® server: SAP Sybase IQ is planned to deliver data management for “big data” analytics, offering extreme total cost of ownership (TCO). Progressive integration with SAP HANA is intended to provide a smart store for aged/cold data. SAP Sybase IQ is envisioned to share common capabilities and life-cycle management with the SAP HANA platform.
  • SAP® Sybase® SQL Anywhere: This market-leading mobile and embedded database with millions of deployments is planned to be the front-end database for the SAP HANA platform, extending its reach to mobile and embedded applications in real time.
  • SAP® Sybase® PowerDesigner software: This flagship data modeling, information architecture and orchestration software is envisioned to become the foundation of the modeling solution for the SAP real-time data platform, offering a large base of experts to customers. Ford Motor Company recently selected the software to drive its data modeling and management and centralize all logical and physical modeling functions.
  • SAP® Sybase® Event Stream Processor (ESP) software, SAP® Sybase® Replication Server and SAP solutions for EIM: Combined, these offerings are intended to provide data assessment and integration of batch, real-time change data capture and streaming data into the SAP real-time data platform.
  • SAP real-time data platform integrated with Hadoop: SAP HANA and SAP Sybase IQ are planned to extend support for accessing “big data” sources such as Hadoop, and offer a deeply integrated pre-processing infrastructure

Source :: http://www.sap.com/corporate-en/press/newsroom/press-releases/press.epx?pressid=18621

Sybase ASE Indexes

April 9th, 2012 No comments

Index:

Indexes are the most important physical design element in improving database performance:

Indexes help to avoid table scans. A few index pages and data pages can satisfy many queries without requiring reads on hundreds of data pages.

Indexes in ASE:

We can divide ASE indexes in two categories by : i) Physical Order of Data with index key  ii) Uniqueness of the index column

Based on the physical order of data, Adaptive Server provides two general types of indexes that can be created at the table or at the partition level:

Clustered indexes, where the data is physically stored in the order of the keys on the index:

• For all pages-locked tables, rows are stored in key order on pages, and pages are linked in key order.

• For data-only-locked tables, indexes are used to direct the storage of data on rows and pages, but strict key ordering is not maintained.

Non clustered indexes, where the storage order of data in the table is not related to index keys

Based on index column uniqueness, indexes can be unique and non unique.

So following types of indexes present in ASE with permutation and combination with above two properties:

1. Unique Clustered Indexes

2. Non unique Clustered Indexes

3. Unique Non-clustered Indexes

4. Non unique Non-clustered indexes

 

Clustered Index Non Clustered Indexes
Unique Unique Clustered Index Unique Non Clustered Index
Non – Unique Non Unique Clustered Index Non Unique Non Clustered Index

So, all the indexes come under above 4 types:

 

In case of more than one index column, we can add prefix composite in above types.

Means Composite indexes are those indexes, which are created on more than on one column. Above four types of index can be composite as well.

In the case of partitions, we can categories above types as local and global indexes.Local indexes get created at partition level and table level index called as Global indexes.

Global indexes with one index tree cover the whole table, or local indexes with multiple index trees, each of which covers one partition of the table.

Function-based indexes are a type of non clustered index which use one or more expressions as the index key.

 

SAP will disclose its Database plans on April 10 in San Francisco !!

March 27th, 2012 1 comment

SAP aims to become major database software maker…

* Move will heat up rivalry with Oracle Corp

* May also put SAP at odds with IBM, Microsoft

* To disclose plans at April 10 press conference
German software maker SAP AG says it intends to become a major provider of database software in a move that would heat up its long-running rivalry with Oracle Corp, led by Silicon Valley billionaire Larry Ellison.

SAP said it will disclose its plans at an April 10 news conference in downtown San Francisco, not far from Oracle’s headquarters in Redwood City, California.

The German company is the world’s biggest maker of business management software, which includes programs that manage tasks such as accounting, manufacturing and payroll. While Oracle is the No. 2 player in that market, it sells more software, thanks to its leadership in the multi billion-dollar market for databases.

Source :: http://www.reuters.com/article/2012/03/15/sap-oracle-idUSL2E8EFBU520120315

http://www.zoneic.com/sap-plans-major-database-software-maker-ibm-microsoft-opponent.html

http://sp.m.timesofindia.com/PDATOI/articleshow/12290674.cms

http://misclassblog.com/database-design-and-development/sap-looking-to-take-over-database-market/

http://www.cloudbulletin.com/news/sap-plans-big-for-database-mkt-oracle-rivalry-to-go-fiercer

Oracle Reply : http://articles.timesofindia.indiatimes.com/2012-03-21/strategy/31219619_1_scott-behles-oracle-database-german-software-maker
See the Course Catalog on ASUG Annual Conference @  Orlando, Florida | May 14-16, 2012 , it is probable
SAP is planning to give complete Database Solution by SAP HANA platform, SAP Sybase Adaptive Server Enterprise, the SAP Sybase IQ server, and Sybase SQL Anywhere.

Lets wait on the clarity till Apr 10!!

Happy Reading !!

 

 

 

 

Sybase IQ Installation

March 24th, 2012 No comments

Hi All,

Please find attached Sybase IQ Installation on Unix/Linux platform.

Sybase_IQ_installation

Petabyte Size Data Store Managed by Hadoop & Map Reduce.

February 11th, 2012 No comments

Hadoop
——–

Source : http://hadoop.apache.org/ & www.
Today, we’re surrounded by data. People upload videos, take pictures on their cell phones, text friends, update their Facebook status, leave comments around the web, click on ads, and so forth. Machines, too, are generating and keeping more and more data. You may even be reading this book as digital data on your computer screen, and certainly your purchase of this book is recorded as data with some retailer.

The exponential growth of data first presented challenges to cutting-edge businesses such as Google, Yahoo, Amazon, and Microsoft. They needed to go through terabytes and petabytes of data to figure out which websites were popular, what books were in demand, and what kinds of ads appealed to people. Existing tools were becoming inadequate to process such large data sets. Google was the first to publicize MapReduce—a system they had used to scale their data processing needs.

This system aroused a lot of interest because many other businesses were facing similar scaling challenges, and it wasn’t feasible for everyone to reinvent their own proprietary tool. Doug Cutting saw an opportunity and led the charge to develop an open source version of this MapReduce system called Hadoop . Soon after, Yahoo and others rallied around to support this effort.

What is Hadoop ?
————–

Hadoop is an open source framework for writing and running distributed applications that process large amounts of data. Distributed computing is a wide and varied field, but the key distinctions of Hadoop are that it is

1.Accessible—Hadoop runs on large clusters of commodity machines or on cloud computing services such as Amazon’s Elastic Compute Cloud (EC2 ).
2.Robust—Because it is intended to run on commodity hardware, Hadoop is architected with the assumption of frequent hardware malfunctions. It can gracefully handle most such failures.
3.Scalable—Hadoop scales linearly to handle larger data by adding more nodes to the cluster.
4.Simple—Hadoop allows users to quickly write efficient parallel code.

Comparing SQL databases and Hadoop:
————————————

Hadoop is a framework for processing data, what makes it better than standard relational databases, the workhorse of data processing in most of today’s applications? One reason is that SQL (structured query language) is by design targeted at structured data. Many of Hadoop’s initial applications deal with unstructured data such as text. From this perspective Hadoop provides a more general paradigm than SQL.
For working only with structured data, the comparison is more nuanced. In principle, SQL and Hadoop can be complementary, as SQL is a query language which can be implemented on top of Hadoop as the execution engine.3 But in practice, SQL databases tend to refer to a whole set of legacy technologies, with several dominant vendors, optimized for a historical set of applications. Many of these existing commercial databases are a mismatch to the requirements that Hadoop targets.
Some Implementation of Hadoop for production purpose :
——————————————————

Complete List @ http://wiki.apache.org/hadoop/PoweredBy

Sybase IQ
———
Sybase IQ : http://www.computerworld.com/s/article/9221355/Updated_Sybase_IQ_supports_Hadoop_MapReduce_Big_Data_

EBay
—-

532 nodes cluster (8 * 532 cores, 5.3PB).
Heavy usage of Java MapReduce, Pig, Hive, HBase
Using it for Search optimization and Research.

Facebook
——-

We use Hadoop to store copies of internal log and dimension data sources and use it as a source for reporting/analytics and machine learning.

Currently we have 2 major clusters:

A 1100-machine cluster with 8800 cores and about 12 PB raw storage.
A 300-machine cluster with 2400 cores and about 3 PB raw storage.
Each (commodity) node has 8 cores and 12 TB of storage.
We are heavy users of both streaming as well as the Java APIs. We have built a higher level data warehousing framework using these features called Hive (see the http://hadoop.apache.org/hive/). We have also developed a FUSE implementation over HDFS.

LinkedIn
———

We have multiple grids divided up based upon purpose. * Hardware:
120 Nehalem-based Sun x4275, with 2×4 cores, 24GB RAM, 8x1TB SATA
580 Westmere-based HP SL 170x, with 2×4 cores, 24GB RAM, 6x2TB SATA
1200 Westmere-based SuperMicro X8DTT-H, with 2×6 cores, 24GB RAM, 6x2TB SATA
Software:
CentOS 5.5 -> RHEL 6.1
Sun JDK 1.6.0_14 -> Sun JDK 1.6.0_20 -> Sun JDK 1.6.0_26
Apache Hadoop 0.20.2+patches -> Apache Hadoop 0.20.204+patches
Pig 0.9 heavily customized
Azkaban for scheduling
Hive, Avro, Kafka, and other bits and pieces…

Twitter
——–

We use Hadoop to store and process tweets, log files, and many other types of data generated across Twitter. We use Cloudera’s CDH2 distribution of Hadoop, and store all data as compressed LZO files.

We use both Scala and Java to access Hadoop’s MapReduce APIs
We use Pig heavily for both scheduled and ad-hoc jobs, due to its ability to accomplish a lot with few statements.
We employ committers on Pig, Avro, Hive, and Cassandra, and contribute much of our internal Hadoop work to opensource (see hadoop-lzo)
For more on our use of Hadoop, see the following presentations: Hadoop and Pig at Twitter and Protocol Buffers and Hadoop at Twitter

Yahoo!
——–

More than 100,000 CPUs in >40,000 computers running Hadoop
Our biggest cluster: 4500 nodes (2*4cpu boxes w 4*1TB disk & 16GB RAM)
Used to support research for Ad Systems and Web Search
Also used to do scaling tests to support development of Hadoop on larger clusters
Our Blog – Learn more about how we use Hadoop.
>60% of Hadoop Jobs within Yahoo are Pig jobs.

 

Data_

Categories: News, Sybase IQ Server Tags: , ,

Implementation of Function String in Sybase Replication Server(SRS)

January 30th, 2012 No comments

These experience shared by  Senior DBAs as name mentioned, Hope this  will help you to understand more about function string from implementation point of view in a Replication environment: 
Craig Oakley , Senior DBA.
—————————-

We used function strings when we wanted to replicate all columns to some servers, and only selected columns to other (web-facing) servers. This was particularly useful before Rep Server allowed multiple RepDefs on the same table. One concern was text columns which were not being replicated to the web-facing server: we had to create a function string to get a text pointer (we used a one-row table and just update all the text columns on top of each other, as the value was not needed on that server): failure to get a text pointer cause the DSI to go down, and we could not specify that as a condition to ignore.

Beyond this, I would imagine function strings could help specify how you want the update to be done, which could be a performance improvement. It would also allow for a different implementation at the replicate than there is at the primary (such as a table at the primary being two joined tables at the replicate).

 

Sukhesh Nair, Senior Sybase DBA
———————————–

We used to have a setup where data was replicated from sybase to oracle as also to a warm standby sybase server. Rep Server function strings helped in filtering data that would need to be passed to Oracle. It helped immensely in streamlining the data flow to targets by manipulating the incoming data through function string. I feel it is one of the most advanced and useful yet very less used capabilities of Sybase Rep Server.
The deterrent could be because of the complexity it would introduce to the replication system. The setup we had worked wonderfully and never gave us any major problems. Without proper monitoring (which needs to be scripted by DBAs) it used to be hard to maintain. Many of the current Rep Server administrators I see do not have adequate knowledge or experience of handling function strings.

Rey Wang , Senior Sybase DBA
————————-

You can map the delete to no op with functional string.

Partha Gogoi Senior DBA
————————-

We use function strings to transform data at the replicate..We have databases being replicated from Toronto and New York to London, Sydney and Singapore and the client ids are transformed at the replicate because, as per business requirements, the client ids are different at each site.. Of course , having a Universal client id would simplify things , but the systems and databases at each site grew independently until replication was set up and it would be a lot of rework to change all the client ids at the replicate sites

Øystein Grinaker Senior DBA
—————————

A Function String could be used to change default behaviour.
Say you delete a row in a table on PDB, but you do not want to delete the row on the RDB. Then make a change in rs_delete. You may make the rs delete just to make a logical delete by updateing a deletemarker for that spesific row.

 

Source : Linkedin.com

http://www.linkedin.com/groups/What-are-possible-usage-Function-3955841.S.65585220?qid=4eb177c2-d7e3-4572-9be4-92d640046c6c&trk=group_most_recent_rich-0-b-ttl&goback=%2Egmr_3955841