Tag: syndicated

This was my second year going to SQL Saturday in Pensacola and once again I enjoyed it. I stayed again at the Hampton Inn, and bandwidth sucked again. I remembered this from last year, and it was a struggle to get things done. I might need to pick a new place next year, just for that reason. I couldn’t even answer email most of the time I was here.

I arrived Friday afternoon, went for a run, and then spent some time adding a few notes to my PPTs. They were done, but I find that I always tweak some things as I review the presentations. One of them was being presented for the first time, and so I wanted to be sure that I had notes on all the slides. I had both computers linked to the Internet, hoping that Live Mesh works since most sites, including Google News, didn’t. I ended up leaving both computers running while I headed to the speaker dinner.

As a speaker, I find the Friday night event invaluable. I get to talk with other speakers, find out what they’re doing, what they think of other events, chat about SQL Server, and more. That’s one of the highlights for me, and I get to meet new people as well. This year the event was a a Tiki bar, which was nice, a good outdoor venue until the rain started. We got driven inside, but I still spent some time with the organizers, Rodney and Karla. I met Tim Costello, who I chatted with more Saturday night, and I spent time time catching up with Tim Mitchell and Trevor Barkhouse from Dallas. We mixed talking shop with some games, including Rodney and Karla’s favorite, the alphabet game.

Saturday was the main event day. It’s been held at the local community college both years, and it’s a short walk down from the hotel for me. Even in the Pensacola heat, at 7:00am it wasn’t bad. I had a pre-event session, for people that were early on basic SQL Server. I set up in the auditorium, but the projector was locked and we couldn’t use it. So we parade across the hall to the other building and I set up in a classroom up there.

The session went well, and I’d recommend this to all SQL Saturday organizers. Have a few sessions early that give people something to do. I’d suggest intro sections that can help some beginners get some foundations for the day.

I wandered around during the day until I had my 3pm session. I liked that most all the sessions were close together on the second floor of one building, with one other large auditorium across the breezeway in another building. It made it easy to find things, and also allowed traffic to pass through the entry foyer where a number of vendors had set up. Putting this event close to TechEd (both in timing and distance) meant that Karla had a number of sponsors, Red Gate, Quest, Confio, Telerik, and a few local companies. A good variety, and I was happy to see people talking to vendors.

One note to other organizers, vendors provide you with support, make sure you support them with good placement to meet people.

My presentation went fine, with another 30-40 people that seemed to get some benefits from it. I got some good comments later, and I make it a point to ask people after the session, and in the party, if they found it useful. I got a couple good suggestions and I’ll incorporate them in future talks.

Lunch went smoothly, there were plenty of drinks around in the breezeway all day, though they ran out of water. I’d actually purchase more water since it’s healthier, but there were still drinks available later. Breakfast was only coffee and donuts, and it would have been nice to see some juice or milk available in limited quantities. I know budgets are tight, but there are people that don’t do coffee.

I did take a few minutes after lunch and I wandered down to a room where Beatles Rock Band was set up. I believe this was a giveaway, and it was fun to spend a few minutes in there with some volunteers. I had the guitar and there were a few guys with me. It was fun, but the room was so far away that I’m not sure if many people made the long walk over there.

I left early to run, get changed and check some email before the after party, so I missed the giveaway. I should have stayed since email didn’t work, and just gotten a quick run in. The after party was at Rosies again and I had a good time sitting and chatting with people. I made it a point to spend an hour walking around and  meeting with different groups, and then ended up hanging with the Dallas boys until our bus came later.

Two notes on the event after party. One, Karla had a bus scheduled to take and pick up  a bunch of us from the main hotel. That was a great touch, and it made it so I didn’t need a car. The hotel had an airport shuttle, which is rare, but for those of us from out of town it was great. Two, I know some people love to party, and enjoy the music after the party, but I go to network and it’s hard to do that when there’s really loud music. I’d like it if we could find more casual places for the after event. We did have a couple hours before the band started, so maybe that’s just me. I suppose we could have walked next door somewhere to chat if we wanted to.

Overall it was a great event, and I really enjoyed it. I’m not sure if I’ll go next year since I need to spread around my travel and would like to get to some new cities, but this is one of my favorite SQL Saturday locations.

I left TechEd this morning, actually too early, catching a 7:12am flight from New Orleans to Denver. Which meant a 5am alarm for me, not the most fun after being out with some fellow MVPs last night at the New Orleans Aquarium.

This was a short TechEd for me, combined with SQL Saturday #22 in Pensacola. I was gone 5 days from home, across a weekend, and that was a long trip. So even though I had a great time and enjoyed seeing friends and learning a few things, I was ready to come home. I missed a few sessions that I wanted to see today and tomorrow, but I’ll try to catch recordings online.

TechEd is a crazy conference, a zoo as I noted on Tuesday, with 10,000+ people gathered in one conference center. It’s a big Microsoft conference, covering all sorts of products and technologies. It’s always seemed to me that most of the focus is non-SQL products, with lots of Windows, Exchange, and infrastructure technologies. There are some developer sessions, and definitely some SQL ones, that’s the minority. Even with the Business Intelligence conference co-located with TechEd this year, it seemed that this wasn’t a big SQL conference.

That’s OK, and I had some good sessions on SQL that I saw. I spent one day going to a few regular SQL sessions, and then Tuesday in the BI area, checking out some speakers. The lessons learned from the Canadian Royal Mint was an excellent session and I’m trying to see if PASS can get that session at the Summit this year.

A few of my SQL friends go to TechEd to work on other technologies. Buck Woody (blog | Twitter) said he tends to avoid SQL sessions and go to lots of Windows ones on things like clustering, AD, areas that he does some work in. I had other people hit sessions on hacking, on Integrated Communications, and a few people check out Windows 7 Phone sessions. I think the latter went just to try and decide if they wanted to buy one later this year.

I don’t know if this is a great networking conference for people, unless you already know lots of people going. I did meet a few people, and met a few new Microsoft people, but for the most part I reconnected with people I already knew. Since I only see many of these people 2-3 times a year, it’s a good chance for me to say hi, and perhaps convince a few of them to write me an article or two.

I wasn’t thrilled with the New Orleans convention center, since it felt really long and narrow, requiring a lot of time to get to sessions, but the town was nice. It’s neat walking around downtown, people were friendly, and there’s a lot of history there. I barely scratched the surface, but I’m looking forward to going back in August for SQL Saturday #28 in Baton Rouge and spending a couple days in New Orleans.

Next year TechEd North America is in Atlanta, a city I’ve never spent time in and I hope I get to go again.

It’s the million dollar question. Literally.

I stopped by the SQL Server area at TechEd in the expo to talk to Val Fontana, a Microsoft’ie I’ve known for a few years to talk about the largest, and yet-to-be-released version of SQL Server 2008 R2 known as Parallel Data Warehouse. It’s actually above DataCenter edition, and depending on the configuration, can be up to around $2mm for the appliance, with roughly 90+TB of data.

Literally a million dollar question if you have a large data warehouse.

I went to a deep dive on this product as well, from Matt Peebles, formerly of DATAllegro, which was purchased by Microsoft. Supposedly all of the Linux/IngreSQL/other technology is completely ported to Windows now, and they are almost ready for a V1 release of this version.

A few people had MPP/Shared nothing servers in their environments, but not many. A few definitions to start.

A core concept is shared nothing. Resource and data independence are maintained in each DBMS instance. Google does this, breaking each part of the problem into smaller parts, each part handled on a separate node.

In this instance, each instance has certain shared resources (CPU, memory, disk) that is for only it’s use. Then you can scale out continually to add new resources with another box/instance.

MPP is separate: massively parallel processing. Multiple concurrent resources are used to solve SQL queries. Each instance works in parallel on its own distribution of the data. PDW supports up to 10 parallel instances per data rack (HP appliance, 8 with Dell), limited to 4 racks (40 instances). The reason is that they have only enough to test 40 nodes, but they will go larger. No architectural limitation for 40 nodes.

Comparing this with SMP, theres this slide:

 

A couple interesting points. SMP needs HA architected, but in MPP in PDW, this is built in. This should also scale out to > 1PB+.

Funny to see them listing this as relatively low cost. I guess at $1M+, relatively is the key word.

There also is a note of limited SQL Server functionality. I had heard this earlier, with no stored procedures, no text/image/binary data, no spatial, no XML, just text/numbers/queries, but those are the critical types. Partitioning is supported.

This is also somewhat based on the Fast Track program, where systems are basically configured for you to drop an application on. The workload matters more than the capacity, and it is hard for people to design systems. So the Fast Track and PDW systems are almost turnkey. If you need more SQL Server capabilities, they recommend Fast Track. They can also publish data for smaller marts to Fast Track architectures if you need that. I guess if you have a seven figure budget, what’s a few more DW servers?

Ultra Shared Nothing – Never heard of that, but this is an extension of shared nothing. What’s different?

• IO and CPU affinity within SMP nodes.
• Multiple physical instances of a table
• Distribution of large tables
• Smaller tables replicated
• Rows are redistributed on the fly when needed.

This means the system is balanced, with the right amount of drives and CPU for max throughput. So each node is silo’ed, having each node dedicated to chunks of data. So you max out each node with the best CPU/RAM/DISK possible.

This gives more predictable results on the system. As you add mode nodes, it scales fairly linearly.

This technology is converted from DATAllergro to the Microsoft platform. This locked down on W2K8 SP2, SQL Server 2008 SP1 cu5. This is a software + hardware solution, pre-tuned and optimized, with users seeing 1 server. Specific architecture appliances from HP, Dell, IBM, EMC, and Bull.

This is designed for DW workloads, sequential in nature, read only access. It does do loads, and they have a fast loader, but the workloads should be DW in nature. They support normalized and star schemas. It’s built for large loads, 10TB –> 500TB

It’s an R2 release since they integrate with the R2 products, PowerPivot, SSAS/SSRS/SSIS versions of SQL Server 2008 R2.

They are working with  many 3rd party BI solutions (Informatica, Microstrategy, etc)

The connection from client is using the Data Direct Drivers, not native SQL drivers. This is likely what will ship. They will ship ADO.NET, OLE-DB, and ODBC. Data Direct will provide JDBC drivers.

These drivers talk to the control node. That stores authorization info metadata, workspace for final aggregations, etc. This has the main PDW engine.

The control node talks to the underlying compute nodes. This is over a dual  2GB/s Infiniband bus, which is very fast. The compute nodes also keep a service called DMS, which redistributes data among nodes if needed.

There are also storage nodes, bascially SAN storage, but dedicated to each computer node. Should be connected over dual 4GB/s network, private for the storage.

There is a passive, spare compute node that is there for failover. So there is an N+1 failover. The control node also has a spare node with a Windows cluster.

There are a pair of management nodes that reads AD/DNS info and manages that. It also deals with setup/patching, and can leverage the HPC technologies from Windows for provisioning.

There is a landing zone node, an ETL interface for loading data. Is has an SSIS instance, a loader tool, and a file staging environment with a lot of disk. You can load from external SSIS directly if needed.

Backup node is there to do backups. Some test showing 5TB/hour. It does full and diff backups.

This system is delivered to you in multiple racks. All the control nodes (control, management, backup, ETL) are in a rack and then you have data racks with the compute and storage nodes. To expand, beyond the 8 or 10 compute nodes, you add in more data racks.

This is a major system, and not for most people, but for those that need it, it sounds very cool.

Initial reference architectures from HP are DL360 G6s, 8 hyperthreaded cores, 72GB RAM, 6 300GB disks. Or you can go Dell R610, 8 hyperthreaded cores, 96GB ram, 4 300GB disks. Those are some hefty nodes, and you get 8 or 10 of them!

Depending on storage, you can get up to 100TB in a rack, so potentially a 400TB capacity with 4 racks. You can choose performance (smaller, faster disks), or capacity (larger disks). These are basically going with 450GB or 1TB disks.

There are DMVs provided, and mostly the same as SQL Server, but they add on more information as needed. There will be a SCOM pack released after v1 comes out. There are web based admin tools as well. Customer monitoring tools can pull information from DMVs.

All components are redundant (disk, network, power, stored processors) and Windows Failover Clustering is used. Each rack is a separate cluster, and the management nodes use AD failover technology.

Under the Hood

Under the hood, you decide how to lay the data out. There are two classes of tables: big and small. Smaller tables are replicated on every compute node. For large tables, it gets partitioned out across the appliance. You choose the column to evenly lay out the data across all the nodes. The architecture is only as fast as the slowest node. The column you pick gets hashed and moves data across all nodes.

For each node, the data is actually broken up inside each node. There is some affinity that they get with Soft NUMA and Resource Governer to balance nodes. They actually have separate ports for each core in the processor. In terms of the 8 cores, they separate the data into 8 physical tables on the node, each one aligned with a core.

The data is in a R1 pair, with 8 LUNs corresponding to the cores. This is different than the Fast Track config where this separation is managed by the DBA. It’s done automatically here.  They also ensure that replicated are striped here. tempdb is on dedicated LUNS, t-logs are on separate LUNs as well.

The query processing flow was shown next. As you might expect, it works like this:

• Connect with SQL auth. No Windows auth supported right now.
• The query is parsed.
• Validate the user has rights
• Build an MPP plan next. This is the big deal. They have to build a plan that optimally reads sequentially from the disks with minimal data movement.
• The plan is executed
• data returned (either to control node or not), and streamed to client.

There were some interesting questions, and lots of places where Matt mentioned they would do something in v2 to fix, extend, or optimize things. That makes me nervous, but I had heard great things about DAT Allegro before.

This is a good session to examine if you want to see how things work in detail. Some food notes on the flow that hopefully make it to the recording.

Loads also take place in parallel. might be moved twice, but each compute node can process, convert, hash, and then shoot across Infiniband to the correct node.

What are technology preview customers saying? For one that does credit card processing, they are seeing better than linear performance under concurrency, with virtually no degradation for concurrent loads and queries as they are added together.

There is a DW comparison with a 24 core, SMP server. The PDW is 18x faster on average, with a range of 2x-166x. Multi-hour queries ran in seconds. Note that these queries were run with 1 clustered index only on the tables. No NCIs.

Very cool technology. Can you use it? That’s literally the million dollar question.

The Royal Canadian Mint, in Ottawa, is located at a large castle. How cool is that? Would you want to work there?

They are a $2B corporation, but about $700mm without gold trading/processing, with about 950 employees.

Not the Canadian government, they’re really a mid level manufacturing company. They have 4 different business lines, but are dependent on the economy in Canada.

Has to meet market demand for general coins, they don’t have a choice. For collector items, it’s the reverse. They don’t want to meet demand.  They have foreign business, and compete with other mints. That is an engineered, manufactured to order business.

They have a bullion market, trying to meet demand with extreme fluctuations of demand. A very time sensitive business.

With all this business, they need to make relatively real time decisions to maximize shareholder value.

They need to determine what is needed, and what is important, and how to tell. They also had to make sure these are tools that people will use, so it’s important that things match the people.

A demo of a live connection to their server in Canada. Limited showing of some Performance Point stuff due to business sensitvitiy. Early adopter, going from bare metal to production in 90 days. Technology is the easy part.

People, culture, clean data, those are the hard parts.

One initiative is green, reducing paper usage. So they showed a KPI they built on some measurements of usage of paper. Pages/employee over time. The idea is making this more personal to employees and get them to reduce printing, which uses less power, money, etc.

Another demo on exchange rates. They are a worldwide business, dealing with many countries. So they show daily exchange rates, putting them in the warehouse for use by various reports.

Since 2000, they have worked to make a profit and since 2003, they have turned a profit every month. Every month.

That is impressive.

This tool has been used in meetings, instead of whiteboards, PPTs, etc. This was the way to actually look at metrics, values, and data in real time. Microsoft notes this is a way to stop the static view of the world. The CIO of the mint noted someone came to a meeting with

a PPT and the CEO told him to leave. The value of the dynamic nature of data was very apparent.

Why measure?

Measurement is neutral. It’s just a way of capturing data. But measurement can drive behavior. Knowing the value of something changes the way we do things.

Reasons to measure: compliance, planning, justification, improvement, reward/recognize. These are the types of things you gain from measurement, but think about these when deciding what to measure.

You want to measure what matters. You have the ability to measure almost many things, but most things are useless in your environment. This is a challenge to determine those things that do add value.

Value is a highly subjective term, so you’ll need to work on this.

Not everything is equal, meaning that not each measurement is as valuable as others, and some measures only apply to some parts of your business.

They do look at continuous improvement (from Toyota, kaizen), and defining value from the customer’s perspective. Get lean, and getting more horizontal. Start with the customers and then work backwards.

When you have 300 things that matter, nothing matters. You have to determine what is important, and use those things, Too much information, too many KPIs, it’s a problem. Expect to evolve, and change your metrics quickly as you learn what is important and what matters.

If you want to define what matters, you had better really understand your customers. You had better know what is important to them and how they see your business. At the turn of the 20th century (early 1900s) people delivered ice to customers. If you asked them what they did, they’d say they delivered ice.

Soon after that point, the refridgerator was invented. And none of those delivery guys transitioned to refridgeration. Customers didn’t care about ice, they cared about cold beer, and unspoiled meat.

Seven Deadly Sins of Performance Management

The mint used to be in silos, committing provincialism. Narcissism, measuring what matters to the business, not the customer. A good concept to understand.

Don’t forget the people

Context is our perception of measurement. The same measurement can be positive or negative, depending on the context. The context is the most important part of the system. The tools are important, but the people are critical.

How do you know when the context is positive? When the people start to manage themselves, when they start to use the measurements to change behavior, or improve the way they do things.

You do have to beware of tight linkages between rewards and recognition from measurements. You want to target improvements.

If you want people to share their red lights, you can’t shoot them when the red light goes off. You want a no-fault environment.

Mistakes happen. Don’t celebrate them, but don’t punish. Learn from them. Share them, and make things better.

There is an Enterprise Performance group, on par with other IT groups reporting to the CIO, that has a BI group, a collaboration group, and a workflow group. They are almost halfway between the business and IT groups. They use VS, run Sharepoint, SSAS, etc.,, but the people have to be strong with interpersonal skills to work with others.

If you can’t bet the company on it, don’t publish the number. You have to be sure of the data.

Some key strategies to drive BI forward.

– Need strong and vocal champions, usually at the executive level.

– Every number has a name and a goal on it.

– CFO and COO are primary users.

– Balance out measures, sometimes with conflicting views.

– They went to a broad deployment, using lower cost tools from MS to make sure very desktop can get to some level of BI.

– 100 days of amnesty – don’t overreact to bad numbers. Watch them, investigate, ensure there is an issue and fix it. Don’t shoot someone.

– Scorecards are presented to BoD and executive meetings.

– IT doesn’t “do” BI. The build tools, train users, steward (or act as Custodians) for data, and encourages self-service. IT is more of a mentor.

– Don’t wait for perfection.

– Be willing to revisit solutions

It’s an interesting set of lessons, and a good speaker from the Canadian Mint. If you can watch this session, it might help you get BI off the ground, or decide if it’s something you want to get into.