9:15
Describing the architectures. I am going to stop for today. I have a book signing at 10 and the WIT luncheon later today.

9:11
Unique fault tolerance approach

9:05
Talking about column store, sorting.

9:04
Now execution time increases by 1/3 with 4 nodes instead of doubling.

9:03
Divide rows across all other nodes.

9:02
Execution time will double even with a 100 node system. It’s like partition skew since one node will do double the work.

9:01
Mirror data to another node. One node can fail. Execution time will double.

9:00
Handling Hardware errors
Node failures with shared-nothing. Mirroring is not sufficient.

8:58
Explaining shuffling. This is familiar if you have worked with PDW/APS.

8:54
Joins, four cases depending on how tables are partitioned or replicated. Shuffling in some cases.

8:53
Explaining how a table is executed on all nodes. Same query plan runs on nodes.

8:49
Partitioned parallelism.

8:48
Table replication. Tables are completely replicated on every node of the cluster.

8:47
Can lead to skew

8:46
There is no way to know where a row ends up. Hash key partitioning. Use hash key to determine where rows land.

8:46
Round-robin partitioning. Rows are distributed among storage units. All disks end up with the same number of rows.

8:45
Both shared and shared nothing use partitioned tables. This is the key to parallel processing. What does orthogonal mean?

8:44
Partitioned tables
Basis for scalable execution. Distribute the rows of the table across storage devices.

8:43
Network can limit scaling.

8:42
Shared-Storage
Remote storage, data is separated from compute. Local disks for tempdb.

8:41
Shared-Nothing
Commodity servers and commodity networking. Storage and compute are co-located. Scales indefinitely.

8:40
APS and Azure DW are same software in different hardware form factors.

8:38
Two alternative scalable dw designs
Shared-nothing appliances such as APS
Shared-storage Oracle RAQ, Microsoft SQL DW

8:36
Scalable DW Fundamentals
Partitioned tables, but I think he means distributed tables??

8:35
Appliance is always best performing. Cloud is low cost.
Cloud – no CapEx low OpEx. Conception to insight in hours. Flexibility to scale.

8:34
Now, DW in the cloud.

8:33
DW Appliance, low compliance but high costs. OR roll your own with lots of complexity. That was what available in 2008.

8:32
What is driving datawarehousing. Cheap hardware and increasing amounts of data.

8:31
#bringbackRima

8:20
Time for David DeWitt. Our favorite keynote speaker!

8:28
Today is WIT lunch with Kelly Lockwood Primus. Tonmorrow is board Q&A. Speaker Idol round 2. Fill out your evals!

8:27
New website coming 2017

8:26
We connect, share, and learn. New Brand!

8:25
It’s a place that allows us to share. PASS brand was created in 1999

8:24
Denise McInerney. Our focus has shifted to the entire data platform. What does PASS mean to us.

8:23
Microsoft is our biggest sponsor. We have several Global Alliance Partner including SentryOne and Redgate!

8:22
To much to keep up with. Chapters, VCs, more.

8:21
Around 50% in North America.

8:20
We are one global community. We are growing around the world. SQL Saturday events continue to grow.

8:19
Financial stuff…
We include 87% of the countries of the world in our membership.

8:18
Grant Fritchey on the stage.

8:17
At least the guys wearing kilts are not also wearing high heels.

8:16
This is Kilt Day.

8:00
I am back at the blogging table for day 2.