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

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Dataupia satori server l.jpg

Dataupia™ Satori Server

Features and Functionality Training

Tuesday, March 11, 2014


Introduction what are we doing here l.jpg
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.


Agenda l.jpg
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


Unit 1 technical overview l.jpg
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


1 host client blades and arrays l.jpg

Host System

(with DT client)

1: Host Client, Blades and Arrays

  • OS: Solaris, Windows

  • Database Server: Oracle, MS-SQL Server


1 dataupia client components l.jpg

Host System

(with DT client)

1: Dataupia Client Components

  • Native Database: Oracle, SQL Server

  • Data Loader

  • Dataupia Client Software

  • Database Plug-in

  • Dataupia Drivers


1 dataupia satori server components l.jpg
1: Dataupia Satori Server Components

  • Management Backplane

  • Management Console

  • CLI

  • Database Engine


1 typical dataupia array physical components l.jpg

KVM

1: Typical Dataupia Array - Physical Components

Network Switch

Terminal Server

Additional Components

Dataupia Satori Servers

DA Blade

Loader Blade

KVM

Switched PDU (2)


1 high availability drives l.jpg
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’


1 typical it architecture l.jpg

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


1 dataupia s mpp architecture l.jpg

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


1 query stack transparency l.jpg

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


1 management backplane l.jpg
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


1 global services l.jpg

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


1 dataupia data loader l.jpg
1: Dataupia Data Loader

Host Server

System with DTclient installed

Dataupia Array

dtldr

Binary /CSV


Unit 2 the management console l.jpg
Unit 2: The Management Console

  • General navigation

  • Health of blades and array

  • Administration features

  • Personalization

  • Query management

  • Upgrading blade software

  • Online help


2 general navigation l.jpg
2: General Navigation

Menus

Navigation Pane

Tabs

Health Charts

Statistical Snapshot




2 administration features l.jpg
2: Administration Features

Tab Menus

Unassigned Blades





2 query actions l.jpg
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.




Demo unit 2 the management console l.jpg
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


Unit 3 cli l.jpg
Unit 3: CLI

  • Types of Users

  • Dataupia User Commands

  • Dataupia Support commands

  • Using CLI commands 

  • Writing a script


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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.


3 cli command modes l.jpg
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)


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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.


3 show commands l.jpg
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:


3 array and blade commands l.jpg
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.)


3 other useful commands l.jpg
3: Other Useful Commands

Use ? to check the usage and options.


Demo unit 3 cli l.jpg
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


Unit 4 the dynamic aggregation studio l.jpg
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.


4 general navigation l.jpg
4: General Navigation

Navigation Pane

Detailed Information for Selected Folder

Server Information






Demo unit 4 creating an aggregate with the demo project l.jpg
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.


Unit 5 delegating tables l.jpg
Unit 5: Delegating Tables

  • Data distribution on Dataupia arrays

  • Delegating native database tables to Dataupia


5 data distribution methods for array tables l.jpg
5: Data Distribution Methods for Array Tables

all

hash by column

single

round-robin


5 choosing round robin distribution l.jpg

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


5 choosing all blade distribution l.jpg

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


5 choosing hashed distribution l.jpg

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


5 choosing single blade distribution l.jpg

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


5 delegating tables and data l.jpg
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


5 delegation process overview l.jpg
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


5 creating array tables manually l.jpg
5: Creating Array Tables Manually

At shell prompt:

  • Register a data distribution specification for the array table using the regtable command

  • Create the array table using the dttablecreate command

    In Oracle:

  • Change the name of the Oracle table

  • Create a synonym and/or view in Oracle to the array table


5 manual step 1 distribution commands l.jpg
5: Manual Step 1 - Distribution Commands

  • regtable

  • Register a table with the specified distribution method. If no method specified defaults to round robin.

    • regtable <DT_systemid> <tbname> {single|rr|distmap|all} [col1,]

  • chtable

  • Change a table’s existing distribution method.

    • chtable <DT_systemid> <tbname> {single|rr|distmap|all} [col1,]

  • DO NOT change the distribution method of table with data in it.


5 manual step 2 the dttable command l.jpg
5: Manual Step 2 - The dttable Command

Creates, alters, truncates, drops tables on the Dataupia array

  • Usage

    dttable <command> [-t tablename] [options]

    dttable create -t <tablename> { {-c <column name> <column data type> [, ...] } [...] | -f <column definition file> }

    dttable rename -t <old tablename> -n <new tablename>

    dttable add_column -t <tablename> -c <column name> <column data type>

    dttable alter_column -t <tablename> -c <column name> -n <new column data type>

    dttable rename_column -t <tablename> -c <old column name> -n <new column name>

    dttable drop_column -t <tablename> -c <column name>

    dttable create_index -t <tablename> -i <indexname> {-c {<column name> [, <column name>...]} [...]

    dttable rename_index -i <indexname> -n <new indexname>

    dttable drop_index -i <indexname>

    dttable truncate -t <tablename>

    dttable drop -t <tablename>

    dttable describe -t <tablename>


5 manual step 3 rename oracle tables l.jpg
5: Manual Step 3 - Rename Oracle Tables

  • Rename the Oracle tables so that queries that reference the now-delegated tables bypass the original tables.

    Example:

    my_table1 is now on the Dataupia array.

    Rename my_table1 to my_table1_orig

    Oracle syntax:

    alter table my_table1 rename to my_table1_orig


5 manual step 4 create oracle references to the array table l.jpg
5: Manual Step 4 - Create Oracle References to the Array Table

  • Use the original names as a reference to the array table in one of two ways:

    • Create an Oracle synonym for the array table as a remote object:

      CREATE SYNONYM MYSYNONYM FOR “MYTABLE”@”DTNAS”;

    • Create a view of the array table in Oracle:

      CREATE VIEW MYVIEW AS (SELECT * FROM “MYTABLE”@”DTNAS”);

  • The reference then replaces the Oracle table:

    SELECT * from MYSYN;= SELECT * from “MYTABLE”@”DTNAS”;

    - or -

    SELECT * from MYVIEW;= SELECT * from “MYTABLE”@”DTNAS”;


5 indexing l.jpg
5: Indexing Table

  • Native indexes delegated to Dataupia are retained

  • Additionally, Dataupia uses indexing approaches optimized for large data workloads

  • Disk indexing supports record-based optimized storage and rapid retrieval

  • Dataupia indexing is transparent to the application

  • Optimized Hilbert r-tree Index

    • Built-in index for every table

    • Designed for clustered data in which target rows are physically close

    • Example: time-sequenced data loaded in chronological order and often queried by date or time

  • Balanced Bucket Index (BBI)

    • Explicit definition occurs when you use the dt_cli utility

    • Designed for data in which the target rows are physically dispersed

    • Example: in queries against non-chronological columns such as phone number


Lab unit 5 delegating tables l.jpg
Lab Unit 5: Delegating Tables Table

  • Unload Oracle tables prior to delegating

  • Delegate existing tables using delegator

  • Create and register array tables using dttable

  • Rename tables on Oracle

  • Create and test Oracle view/synonym


Unit 6 dataupia data loader l.jpg
Unit 6: Dataupia Data Loader Table

  • How it works

  • Writing data description files for CSV and binary data

  • Command line options and scripting

  • dtlscan testing utility

  • Potential errors and troubleshooting the Loader





6 data description files l.jpg
6: Data Description Files Table

Description file for CSV (ascii) data file with directive to omit trailing characters

Description file for binary data file with modification directive for first field

%EXTENSION / %ENDEXTENSION is an optional section for defining transformations and operations




6 description file modification directives l.jpg
6: Description File Modification Directives Table

Use int(), string(), and datetime() to modify parsed data as needed. For example:

CALL_DATE int(8) | string(14) | datetime(“%Y%m%d%H%M%S”);

  • Binary data file contains eight-byte binary integers encoding ten-digit decimal timestamps, e.g. timestamp 2007-02-10 16:09:22 is represented as integer 20070210160922 and encoded in the binary value 0x00001240f5b4491a

  • Parsing directive int(8) converts eight bytes of input stream to decimal integer

  • Modification directive string(14) converts digits of integer to 14-character string

  • Modification directive datetime(“…”) converts string to timestamp, with first four characters as year and remainder as two-digit month, day, hour, minute, seconds

  • Field is loaded into Dataupia table column CALL_DATE of type timestamp


6 scripting the loader l.jpg
6: Scripting the Loader Table

Here is a script to

  • load all data files with extension .data from directory datadir

  • load into table bigtable on array with ID 12345678

  • using description file bigtable.f

  • logging to bigtable.log

  • writing information about loaded files to array table loaded_bigtable

  • writing information allowing for 10 error records to bad_records_bigtable

find datadir -name "*.data" | dtldr –C dtarrayid=12345678 -D bigtable.f -T bigtable -E 10 -L bigtable.log



6 loader diagnostics l.jpg
6: Loader Diagnostics Table

  • Use the –T option for dtldr to name status tables and specify templates

  • loaded table

    • fkey A file key (integer) to identify the bad record’s source

    • fname Name of data file (varchar(200)) passed to the loader

    • fmtime The file’s system time (timestamp without time zone)

    • nrecords Number (bigint) of records in the specified data file

  • bad record table

    • fkey A file key (integer) to identify the bad record’s source

    • field Name (varchar(120)) of the field being parsed when the error was detected

    • rec_offset Offset (bigint) from the beginning of the data file (in bytes) of the bad record

    • error Code (integer) describing the nature of the error

    • input_data The bad record as a hex-encoded string (varchar(32000))


6 dtlscan utility l.jpg
6: dtlscan Utility Table

dtlscan –D data_description -f data_file [–p –E –o –t –n –e -r]

Scans, analyzes and converts data files using data description files to predict or isolate errors

encountered by dtloader. Does not interact with the database server or the array.


6 potential data loader problems l.jpg
6: Potential Data Loader Problems Table

  • Description File

    • Syntax errors

    • Does not match input data

    • Does not match target table

    • Field needs further modification to be compatible with target column

  • Data Errors

    • NULL data

    • Mismatched or unsupported format

    • Illegal value


6 troubleshooting l.jpg
6: Troubleshooting Table

  • Four ways to investigate errors

    • Use dtlscan with –p and –E options to verify description file and isolate bad records before loading.

    • Review the loaded files table on the array for information about data files loaded into the target table.

    • Review the bad records table on the array for information about records that could not be loaded into target-table and generated an error.

    • Use the dtldr–llogfile option to write information about errors to a log file and review the log contents.

  • Setting the error limit with the dtldr –E [-]count option

    • Negative count - # of errors to record before dtldr aborts

    • Positive count - # of errors to record before dtldr stops recording (but continues execution)


6 the dtunload command l.jpg
6: The dtunload Command Table

  • Purpose

    Unloads data from Dataupia array tables. Useful for archiving or back-ups.

  • Usage

    dtunload -C “dtarrayid=<array_ID>” -q “<query>” [-o <options>]

  • Arguments

    <array_ID> Array ID of the array on which the table is located

    <query> Query to obtain desired rows from table, of the form select <col1>[,col2,…] from <table>

    <options> Options for formatting unloaded data, including –CSV for CSV format and options to specify

    delimiter, null, quote, and escape characters

    • Arguments with spaces or other separators must be quoted.

    • Default is standard output. Redirect to a file.

  • Example

    dtunload -C "dtarrayid=62674212" -q 'select * from table23' -o "CSV DELIMITER '|'" > myfile


Lab unit 6 loading data l.jpg
Lab Unit 6: Loading Data Table

  • Analyze and understand input and data description files

  • Use dtlscan to test and correct adescription file

  • Write a data description file

  • Use dtldr to load data

  • Review results of load including loaded_ and bad_records_ tables on the array

  • Truncate target table, fix errors, and reload


Unit 7 troubleshooting l.jpg
Unit 7: Troubleshooting Table

  • RAID-5 failover

  • Replacing a failed drive

  • Troubleshooting network problems

  • Restarting a blade

  • Replacing a blade

  • Getting support


7 raid 5 disk drive failover l.jpg
7: RAID-5 Disk Drive Failover Table

  • Each blade has eight drives - seven active drives in a RAID5 configuration + one hot spare

  • If a drive fails, RAID fails over to the spare, no data lost

  • Blade operates in degraded mode (low disk space, degraded performance) until failed drive is rebuilt on spare

  • After rebuild, the spare should be replaced as soon as possible


7 replacing a failed drive l.jpg
7: Replacing a Failed Drive Table

  • Directly verify that you are working on correct blade

  • Locate drive to be removed

  • Record number/location of failed drive

  • Move release lever to right and pull on release tab

  • Pull drive by gripping with fingers and pulling out

  • Push new drive into bay as far as possible, close release lever fully

  • The new drive becomes the hot spare


7 troubleshooting network problems l.jpg
7: Troubleshooting Network Problems Table

  • ping blade with suspected problem from another device on the network (or all blades if problem is not yet isolated).

  • If ping fails, confirm that blade is on and operating.

  • Connect keyboard/monitor and try ping from suspect blade.

  • Check blade’s cable connections to the network switch. Are lights green at both ends? Try replacing cable or a different switch port.

  • Try bypassing switch and connecting directly to network. If blade’s HBA has failed, chassis must be replaced.

  • Use the blade restart command to restart network services, or blade reload for a warm reboot.


7 restarting a blade l.jpg
7: Restarting a Blade Table

Different restart commands have different effects:

  • blade restart

    Restart all services on the local blade.

    If issued with globalsvcs argument, restart only global services.

  • blade reload

    Reboot the blade without powering it off (”warm restart”)

  • blade shutdown

    Shut down the blade and power it off (turn on again to reboot)


7 replacing a chassis l.jpg
7: Replacing a Chassis Table

  • If you have eliminated a failed drive or network issue as the root problem, the chassis must be replaced.

  • Generally a chassis must be replaced if the CPU, HBA, memory, disk controller, power supply, or fan fails.

  • The array will be inaccessible while the chassis is getting replaced.

  • No data loss is incurred by a chassis replacement.

  • Contact Dataupia Support to arrange for chassis replacement.


7 getting support l.jpg
7: Getting Support Table

  • Information resources

  • Logging a case

  • Checking status

  • Communication


7 finding information l.jpg
7: Finding Information Table

  • Product Usage

    • Product Documentation

    • DMC Online Help

    • Release Notes

    • Knowledge Base

    • Engineering Briefs

  • Troubleshooting

    • DMC Health Tab

    • Release Notes

    • Dataupia Satori Server User Guide, Chapter 5, “Troubleshooting”

    • Knowledge Base

    • Log Files


7 logging a case l.jpg
7: Logging a Case Table

The Dataupia Helpdesk is staffed 9-6 EST (GMT-5)

  • Phone: 866-259-5971

  • Email: [email protected]

    The Portal is always open:

  • http://www.dataupia.com

    Click the Customer Login link at the top right of the window.

Password provided to you by Dataupia



7 logging a case84 l.jpg
7: Logging a Case Table

Helpful information to include in the Description field:

  • DataupiaTM Satori Server serial number

  • Contact information for the person that will troubleshoot the problem with the Dataupia Support Engineer

  • Error codes recorded on the equipment displays or trapped by the host

  • What has been done so far to isolate the problem


7 reviewing cases l.jpg
7: Reviewing Cases Table

Double-click on a Case number to view status or solution and provide additional information

Knowledge base of Solutions


Summary l.jpg
Summary Table

  • Survey

    • Is there anything else we should add to class?

    • Do you feel confident about what you learned?


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