Tech Talks – DB2 for Linux, UNIX and Windows

by Sajan Kuttappa, Content Marketing Manager

IBM DB2 for Linux, UNIX and Windows database software is the foundation that powers many IBM Analytics offerings. In conjunction with the International DB2 Users Group (IDUG®), the DB2 product team hosts a series of monthly webinars highlighting key capabilities, use scenarios, and various aspects of data management needs. Below, you will find a listing of past webinars and upcoming topics. If there are topics that you would like us to cover, please email us at ibmdatamgmnt@gmail.com

2017
Topic Presenters
Managing your DB2 on Cloud environment Kelly Schlamb
Extending SQL: Exploring the hidden JSON capabilities in DB2 George Baklarz
Jump Start 2017 with a new DB2 11.1 Matt Huras, Roger Sanders
2016
Topic Presenters
dashDB for Transactions – Fully managed Andrew Hilden
DB2 on the Cloud – Moving to the cloud with full control Jon Lind, Regina
BM DB2 on SAP – V11.1 Update and Recent Developments Karl Fleckenstein
DB2 Security: From the Data Center to the Cloud Roger Sanders
DB2 Tech Talk: Data Server Manager and DB2 connect Mike Connor, Anson Kokkat, Shilu Mathai
DB2 Tech Talk: DB2 V 11 performance update Peter Kokosielis
DB2 V11.1 Deep Dive on BLU & Analytics Enhancements John Hornibrook, David Kalmuk
Breaking scalability barriers: A DB2 V11.1 Technology Review Matt Huras / George Baklarz
DBaaS for Developers on IBM Cloud. Andrew Buckler
Can you use your SQL skills for big data? Paul Yip
What’s New in IBM Data Server Manager V1.1.2 Anson Kokkat

DB2 with BLU Acceleration and Intel – A great partnership!

Allen Wei

Allen Wei, DB2 Warehousing Technology, System Verification Test, IBM

DB2 with BLU Acceleration is a state of art columnar store RDBMS (Relational Database Management System) master piece that combines and exploits some of the best technologies from IBM and Intel. In the video linked below, there is mention of an 88x speedup when compared with the previous generation of row store RDBMS on the exact same workload. That announcement was made during IBM IOD in November 2013.

Guess what? In a test done a few days ago (less than 3 months after the video was filmed), the speedup, again comparing DB2 with BLU Acceleration with row store RDBMS using the exact same workload on new Intel Xeon IVY-EX based hardware, is now 148x. Really? Need I say more? This shows that not only is DB2 with BLU Acceleration equipped with innovative technologies, but it also combines the exact set of technologies from both RDBMS and hardware advancement that you really need. This helps BLU Acceleration to fully exploit hardware capacities to the extreme and to give you the best ROI (Return on Investment) that every CTO dreams about.

You might start wondering if this is too good to be true. I have shown you the numbers. So, no, it is the truth. You might want to ask, even if this is true, is it complicated? Well, it does take discipline, innovative thinking and effort to offer technologies like this. However, my answer is again a No. It’s completely the opposite! In fact, As Seen on TV (the video clip), it’s as simple as – create your tables; load your data and voila!! Start using your data. There is no need for extensive performance tuning, mind-boggling query optimization or blood-boiling index creation. Leave these tasks to DB2 with BLU Acceleration.  Can’t wait to try for yourself? It really is that fast and simple.

Do you need to hear more before you are 100% convinced? Let me begin by recalling a few key disruptive technologies that are built into DB2 with BLU Acceleration. This is mentioned in the video clip as well, and I will prove to you that we are not listing for the sake of listing them.

What state of the art technology was built into DB2 with BLU Acceleration that makes it so great? Here is a summary of what you saw on in the video clip:

# Dynamic In-Memory Technology – loads terabytes of data into random access memory instead of hard disks, streamlining query workloads even when data sets exceed the size of the memory.

  • This allows the CPU to operate efficiently without waiting on the disk I/O operations
  • In my case, for one instance, I could fit 2TB database into 256GB RAM or 1/8 of the database size
  • I could also fit a 10TB database into 1TB RAM or 1/10 of the database size, in another test.

# Actionable Compression – Deep data compression and perform actions directly on uncompressed data

  • Deep compression
  • I noticed a storage space consumption that was 2.8x – 4.6x smaller than corresponding row-store database, depending on the size of  the database
  • Data can be accessed as is in the compressed form, no decompression needed
  • CPU can dedicate power to query processing not on decompression algorithms.

#  Parallel Vector Processing – Fully utilize available CPU cores

  • Vector is processed more efficiently hence there’s an increase in CPU efficiency
  • All CPU cores are fully exploited.

#  Data Skipping – Jump directly to where the data is

  • We do not need to process irrelevant data.

Have  you been convinced, yet? I know you have. However, you don’t need to just take my word for it. Try it. The time you spent on reading the blog and trying to find a loophole is enough to give yourself a high performance database from scratch. Period.

Read more about the Intel and BLU Acceleration partnership here : DB2 BLU Acceleration on Intel Xeon E7v2 Solutions Brief 

Allen Wei joined IBM as a developer for the BI OLAP product line, including OLAP Miner. He was a key member of the Infosphere product line, and has lead Infosphere Warehouse and DB2 LUW SVTs. Currently  he focuses on tuning the performance of BLU Acceleration, mainly w.r.t the Intel partnership.

Visit the IBM BLU HUB to learn more about the next gen in-memory database technology!

Also checkout this post on the Intel Blog about how IBM and Intel have been working together to extract big data insights.

A BLU Valentine

Vineeth

Vineeth George Abraham
Product Marketing, Data Management, IBM

Valentine’s Day is here, once again. A day to celebrate love – be it with family, friends or partners. A day to take a break from the mundane and spend time with the ones you care about.

For a day, everything seems possible when you celebrate that feeling of togetherness and endearment that we term as love. But if you are anything like me, there’s a part of this day that you’ll always dread. Why?

Deciding on a gift or an experience for someone close to me,  is not an activity that I’m terribly excited about. It’s not because I don’t care. Au contraire! It’s because I invariably  get confused while selecting something meaningful; and this exercise turns out to be a lot harder eventually , than it initially looks.

There’s a ton of options out there. But, what gift or gesture would have the most meaning? This struggle with choice rears its head like clockwork, on every birthday and anniversary too. I’d be thrilled  just to get a useful suggestion, when faced with this situation.

At least, it’s highly improbable that you’ll forget Valentine’s day, unlike some birthdays or anniversaries. You will get reminders in passing during your coffee breaks, your lunches and even in general water-cooler conversations. The steady stream of messages through various media, and the general buzz in the air makes sure that only hermits probably somewhere in the Himalayas or the Andes stay oblivious to the effects of Valentine’s Day.
Phew, that’s a minor relief. Forgetting one of these days might get you the cold shoulder treatment for a while. Brrr…. Now that I think about it, a stint in the Himalayas for a week might actually be a bit more bearable!

I digress… Now where was I? Ah yeah…Plans, gifts.When I think of experiences, I tend to oscillate between extremes before finally settling somewhere in the middle. Do something adventurous (skydiving, ‘jumps’ to mind) or stick closer to terra firma, with a dinner and a movie?

The interesting bit is that all the hints and signals, for a great experience were probably shared with you. If you had paid attention to all the conversations, the tweets, the calls, the glances, a comment made in passing you’d have had your answer.

It’s in times like these, that I’ve come to yearn for an assistant like Jarvis, from Iron Man. Imagine how useful he’d be. A voice in your ear : ‘Sir – from my analysis of your phone calls, Facebook, twitter, credit card transactions etc. etc…. there’s a high probability that he/she would be thrilled to go 1-Spelunking or 2-dancing!’  Dancing it is, then! Problem solved, in seconds. Wouldn’t it be fantastic if you could call upon someone like that in your daily life?

Let’s see what happens in an enterprise environment.

The amount of data that an average enterprise generates and sifts through is huge, in Peta/Zeta bytes! What if there were a way to crawl quickly through all that data – get useful nuggets of information and meaningful insights?

It’s not just enough that data is stored efficiently. It should be easily available to access, manipulate and compare. The right insight at precisely the right time can be a game changer in most industries.

With DB2 and BLU Acceleration – IBM can deliver just that. Part of the larger Watson Foundations solutions, BLU Acceleration in DB2 will help you get better insights faster.  What’s great about DB2 and BLU Acceleration is that along with the robustness and great compression that you’ve come to expect for transactional workloads, you can now have faster analytics and data warehousing capabilities to boot. With it’s noSQL capabilities, DB2 can now deal with data in various formats.

Your data is secure, stored efficiently and you can derive insights extremely quickly.  With a cloud solution for BLU Acceleration, data warehousing capabilities can now be accessed easily with as little overhead cost as possible.

Sometime in the near future I am sure that a portable system similar to Jarvis, with BLU Acceleration DB2 and a host of IBM technologies in the background, will be reality. The IBM Watson programme is a certainly a leap in the direction of cognitive computing.

Here’s an interesting Valentine’s Infographic on Data Management and BLU Acceleration. Enterprises could do with a bit of love too. Share the love – and the infographic!

6 More ways to love Big Data

In the meanwhile, let me get back to prepping for 14/2/14…

Learn more about DB2 and BLU Acceleration on our Google+ page.
Follow Vineeth on twitter @VinGAbr

It’s Obvious. It’s in the Data.

Bill Cole

Bill Cole, Competitive Sales Specialist,Information Management, IBM

You’ve had that experience, right?  Somebody says that the answer is in the data so you look harder and all you see is stuff.  There’s not a pattern within a grenade blast of this data.  Maybe if you had a bit more time you’d find it.  Or maybe having the data in the right format would make a difference.

 We all know the traditional relational database isn’t a great platform for analyzing mass quantities of data.  Your OLTP relational database is built for processing small-ish transactions, maintaining data integrity in the face of an onslaught of concurrent users all without regard to disk space or processor utilization.  Abuse the resources to get the performance you need!  To paraphrase John Paul Jones: Ignore the checkbook, full speed ahead!

So we learned to build special-purpose structures for our non-transactional needs, and then manage the fallout as we tried to find anything that even smelled like (consistent) performance.  Each step forward in the data warehouse arena was a struggle.  We demanded resources or explained away failures with a wave of a disk drive or processor.

This situation was clearly not good for our mission of analyzing great chunks of data in a reasonable time.  Subsets of data – data marts – were used to work around our limitations.  But this meant we were either replicating data or losing some data that might be useful in other queries.  Clearly not the best of situations.

Our friends out in Almaden studied the problem and found that column-oriented tables were the best basis for a solution.  After all, we were gathering up large quantities of raw data and analyzing it, not processing OLTP transactions.  There would be little need for those annoying special-purpose structures.  Nor would we need any indexes.  All this would save lots of space and reduce processing time, too, so we could achieve not only predictable performance but VERY good performance.  The kind of performance our friends in the business needed to build better relationships with suppliers and customers.

The implementation of the new analytics platform is in DB2 10.5 with BLU Acceleration (The answer to why “BLU” is in an earlier blog entry.).  The very cool thing is that BLU is an option you can choose for either the entire database or just the analytics tables.  So you can have your traditional row-oriented tables and the column-oriented tables in a single database if that suits your design.  No need to learn and maintain a whole new technology just for your analytics.

And we can’t forget the synergy with Cognos.  After all, the two products are developed just a few miles from each other.  Turns out the Cognos folks help the DB2 team by sharing typical analytics queries and the DB2 team uses those examples to tune the query engine.  Nice!  Of course, this helps out with the queries we build ourselves or through – gasp!  – other products.  Oh well, DB2 is there to make us all look good.

A quick refresher on column-oriented data.  The easiest way for me to think about it is that we’ve stood the database on its side so that instead of seeing everything in rows we’re seeing the data in columns grouped together.  A typical description of a table has the column names running across the top of the page which is analogous to the way data is stored in a most relational databases.  However, the column-oriented table has the data for a column grouped together and the rows are built by assembling the data from the columns.  Not ideal for OLTP but excellent for processing gobs of data that’s particular to a group of columns.  (There’s a fuller discussion of this in a previous blog post.)  No need for indexes since we’re not looking for individual rows.

The sort of performance users have reported with DB2 and BLU Acceleration, is nothing short of amazing.  Double-digit improvements in throughput.  And it’s this reliably predictable performance that allows us to build those applications that require sub-second kind of analysis.  You know the ones I’m talking about.  While you are on the phone or a web site, the agent or the site offers you options based on YOUR previous interactions, not just options for any random caller or user.  The options are specific because we can analyze data in the time you’re on the phone or a web site.

Finally, I’m told the mark of genius is being able to connect seemingly random dots into a pattern.  You know those folks who are at the conclusion while the rest of us are still just looking at the dots.  You don’t need a genius if you’ve got BLU!  You’ll find that pattern/information gem in record time, too.  And you’ll show the business that you’re delivering the data they need when they need it.

Know more about the innovative technology in BLU Acceleration through this video series on YouTube!