Features and Functionality Training

1. Dataupia™ Satori Server Features and Functionality Training Tuesday, March 11, 2014

2. Introduction – What Are We Doing Here? • 1 day course • Features & Functionality of Satori Blade • Hands-on labs • Goals • Integrating with Host Database • Working with a Dataupia Array • Non-goals • Deploying a Dataupia Array • Supporting a Customer Deployment • Extensive Troubleshooting • Logistics • Restroom, food, breaks, phones, etc.

3. Agenda • Unit 1: Technical Overview • Unit 2: The Management Console -- Demo • Unit 3: Using the CLI – Demo • Unit 4: The Dynamic Aggregation Studio -- Demo • Unit 5: Delegating Tables -- Lab • Unit 6: Loading Data -- Lab • Unit 7: Basic Troubleshooting

4. Unit 1: Technical Overview • Host Client, Blades and Arrays • High Availability - Drives • Typical DBMS Stack • MPP Database Architecture • Query Stack • Dataupia Data Loader • Host DB Connectors: Oracle, SQL • Management Back Plane

5. Host System (with DT client) 1: Host Client, Blades and Arrays • OS: Solaris, Windows • Database Server: Oracle, MS-SQL Server

6. Host System (with DT client) 1: Dataupia Client Components • Native Database: Oracle, SQL Server • Data Loader • Dataupia Client Software • Database Plug-in • Dataupia Drivers

7. 1: Dataupia Satori Server Components • Management Backplane • Management Console • CLI • Database Engine

8. KVM 1: Typical Dataupia Array - Physical Components Network Switch Terminal Server Additional Components Dataupia Satori Servers DA Blade Loader Blade KVM Switched PDU (2)

9. 1: High Availability – Drives • OS - Loaded on internal Flash Drive • Data Storage - 8 hot swappable drives Flash Drive RAID Controller – RAID-5 hot spare Read-only Flash drive with 2 boot partitions used for OS. 7 drives in RAID-5 array 1 drive allocated as ‘hot spare’

10. Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users SUN SUN ERP SAP, Oracle AppsSieble, JD Edwards DSS MicroStrategy, Cognos, SAS, SPSS, etc. “Home-grown” Applications wintel Users Users Users Users Users Users Hitachi HP EMC NetApps 1: Typical IT Architecture Storage Platform Database Existing Oracle Database Existing Oracle Database Standard App Interface (ODBC, JDBC, SQL) Standard Interconnect Interface (SAN / NAS) Existing MS-SQL Database

11. Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users Users SUN SUN DSS MicroStrategy, Cognos, SAS, SPSS, etc. “Home-grown” Applications ERP SAP, Oracle AppsSieble, JD Edwards wintel Users Users Users Users Users Users Record based system Record based system Record based system Record based system Record based system Database Engine Database Engine Database Engine Database Engine Database Engine Dynamic Indexing Dynamic Indexing Dynamic Indexing Dynamic Indexing Dynamic Indexing 1: Dataupia’s MPP Architecture Dataupia Satori Blades Platform Database Existing Oracle Database Standard App Interface (ODBC, JDBC, SQL) Dataupia Drivers Existing Oracle Database Existing MS-SQL Database

12. HS Database Abstraction Oracle Optimizer ODBC Driver Manager dtODBC Driver Record based system Record based system Record based system Record based system Record based system Database Primitives Database Primitives Database Primitives Database Primitives Database Primitives Dynamic Indexing Dynamic Indexing Dynamic Indexing Dynamic Indexing Dynamic Indexing Replication Replication Replication Replication Replication 1: Query Stack - Transparency Host Server GlobalServices Dataupia Array Existing Oracle Database Management Back Plane

13. 1: Management Backplane • Provides wrapper for OS – user has a protected shell • Compact Flash drive (2 OS images on blade) • Diagnostic utilities • Broadcast upgrades (new image installed to non-booted partition) • Centralized Management Framework • CLI language

14. Application Application Users Users Users Users LocalStorage Storage 1: Global Services Bind blades into an array • Root Service • Blade Service • Database Service • ID Service • Transaction Service Blade Daemon runs on each blade Existing Database DT Client Dataupia Satori Blade DataupiaGlobal Services

15. 1: Dataupia Data Loader Host Server System with DTclient installed Dataupia Array dtldr Binary /CSV

16. Unit 2: The Management Console • General navigation • Health of blades and array • Administration features • Personalization • Query management • Upgrading blade software • Online help

17. 2: General Navigation Menus Navigation Pane Tabs Health Charts Statistical Snapshot

18. 2: Health of Blades and Array

19. Blade Health

20. 2: Administration Features Tab Menus Unassigned Blades

21. 2: Personalization

22. 2: Notifications

23. 2: Query Management

24. 2: Query Actions • TerminateForces a query process to terminate within a short time, giving it a chance to finish its work and produce partial results before ending • KillEnds a query process immediately, with no chance for any results • Raise PriorityGives a query process a higher processing priority on the array, which may enable it to fully execute at a normal or near-normal rate • Lower PriorityLeaves a query process active (for example, if you want to preserve the current situation for further analysis) but lessens its impact on overall system performance.

25. 2: Upgrading Blade Software

26. 2: Online Help

27. Demo Unit 2: The Management Console • Configure health charts, warnings, logging • Set up email recipients • Review and take action on queries • Upgrade the software image

28. Unit 3: CLI • Types of Users • Dataupia User Commands • Dataupia Support commands • Using CLI commands  • Writing a script

29. 3: CLI Overview • Provides alternatives to the DMC for information and some actions • Connect a keyboard and monitor to the blade, or use an SSH connection to the head blade’s IP (same address you load in your browser for the DMC • Log in with the same username & password as on DMC • Three modes: standard, enable and configure • Interactive help lets you check the usage and options for any command and subcommand.

30. 3: CLI Command Modes Standard mode Active when you first log in. Enable mode Enter with enable command. View all available information. Take some actions but not configuration changes. Configure mode Enter with configure terminal command. Make configuration changes. Prompts indicate mode you are in: • blade101 > (standard) • blade101 # (enable) • blade101 (config) # (configure)

31. 3: Command Help and Completion • Enter ? on the command line to see a list of commands available in the current mode. • Use ? following a partial word to narrow the list; for example t? in standard mode displays terminal, telnet, traceroute commands. • Follow a command or subcommand with ? to see usage and options. For example, in configure mode: blade101 (config) # image ?boot Specify which system image to boot by defaultfetch Download a system image from a remote hostinstall Install an image file onto a system partition blade101 (config) # image boot ?ocation Specify location from which to boot systemnext Boot system from next location after one currently booted blade101 (config) # image boot location ?1 Boot from location 12 Install to location 2 • Use Tab key to complete unambiguous commands, options, and arguments.

32. 3: Show Commands Use show to display information about the blade you are logged into and the array it is part of. Use ? to check the usage and options. Important show commands:

33. 3: Array and Blade Commands These commands let you configure the blade and the array. (Remember to use ? to check the usage and options, and see the User Guide.)

34. 3: Other Useful Commands Use ? to check the usage and options.

35. Demo Unit 3: CLI • Log in and use different CLI modes • Use show commands to display available information about the array, blades, other arrays, software images, and various settings • Configure email notification settings • Kill a query • Display the logging configuration

36. Unit 4: The Dynamic Aggregation Studio • You can use the DA Studio to create Aggregates, or Data Cubes • With Aggregates you can view and manipulate data in multiple dimensions. • Aggregates consist of dimensions and measures. • Measures – items that are counted, summarized, averaged, etc., such as costs or units of service. • Dimensions – the columns that the measures will be grouped by, such as dates or locations.

37. 4: General Navigation Navigation Pane Detailed Information for Selected Folder Server Information

38. 4: Select Input Data

39. 4: Select and Compile Dimensions

40. 4: Create and Build the Aggregate

41. 4:Query the Aggregate

42. Demo Unit 4: Creating an Aggregate with the Demo Project. • For training purposes, a demo project is provided as part of the Dynamic Aggregation Studio installation. • The demo project comes with an input data file already loaded. • In this demo we will create an aggregate using the demo project.

43. Unit 5: Delegating Tables • Data distribution on Dataupia arrays • Delegating native database tables to Dataupia

44. 5: Data Distribution Methods for Array Tables all hash by column single round-robin

45. 1,5,9,13 … 2,6,10,14 … 3,7,11,15 … 4,8,12,16 … 5: Choosing Round-Robin Distribution • Records are distributed serially and uniformly across blades -one row to each blade in repeated sequence. • The default method. • Records are distributed this way: • Guarantees* even distribution of data across blades with no data analysis required. • Use when there is no ‘natural’ distribution key. • Best suited to fact tables. Blade 1 Blade 2 Blade 3 Blade 4

46. 1,2,3,4 … 1,2,3,4 … 1,2,3,4 … 1,2,3,4 … 5: Choosing All-Blade Distribution • Tables are co-located on every active blade in the array. All records are copied to all blades. • Records are distributed this way: • Required for dimension tables that participate in joins • Ensures that fact:dimension joins will process in parallel and not require cross-blade execution Blade 1 Blade 2 Blade 3 Blade 4

47. 1,9,12,15 … 3,6,11,16 … 2,7,8,14 … 4,5,10,13 … 5: Choosing Hashed Distribution • Records are distributed by a deterministic hash function using the specified column(s) as distribution key. • Record distribution depends on key but should be close to even: • Requires unique or nearly unique distribution key to ensure acceptably even distribution. • The distribution key must be non-volatile and not nullable, as well as unique or nearly unique. Blade 1 Blade 2 Blade 3 Blade 4

48. 1,2,3,4 … 5: Choosing Single-Blade Distribution • Each table is located entirely on a single blade • Records are distributed this way: • Single distribution is appropriate for smaller tables and less frequently used tables Blade 1 Blade 2 Blade 3 Blade 4

49. 5: Delegating Tables and Data • Extract Oracle tables to CSV (or Binary) files • Register a table’s data distribution method • Create the table on the array, including indexing • Create synonym or view in host database

50. 5: Delegation Process Overview Host DB Dataupia array Table A Table A data data delegation dttable & regtable Table B Table B data data data A Extract dtldr data B