Microsoft Data Science SummitSept 26 – 27 | Atlanta, GA

Taming the Data Science Monster with A New ‘Sword’ – U-SQL

Michael RysPrincipal Program Manager Big Data@MikeDoesBigDatausql@microsoft.comhttp://aka.ms/azuredatalake

Agenda Today (BR014): Introduction to Azure Data Lake and U-SQL What is Azure Data Lake? Why U-SQL? Core concepts

Schema on read on file and file sets C# extensibility SQL with U-SQL Script level execution and optimization

Tool usage

Tomorrow (BR013): Killer extensibility in Azure Data Lake with U-SQL Custom rowset aggregation How to do JSON processing Image processing How to call R from U-SQL

The Data Lake approach

Ingest all data regardless of requirements

Store all data in native format without schema definition

Do analysisUsing analytic engines like Hadoop

Interactive queriesBatch queries

Machine LearningData warehouse

Real-time analytics

Devices

Introducing Azure Data LakeBig Data Made Easy

WebHDFS

YARN

U-SQL

ADL Analytics

ADL HDInsight

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Store

HiveAnalytics

Storage

Azure Data Lake (Store, HDInsight, Analytics)

Azure Data Lake & U-SQL

Why U-SQL?

Some sample use casesDigital Crime Unit – Analyze complex attack patterns to understand BotNets and to predict and mitigate future attacks by analyzing log records with complex custom algorithmsImage Processing – Large-scale image feature extraction and classification using custom codeShopping Recommendation – Complex pattern analysis and prediction over shopping records

using proprietary algorithms

Characteristics of Big Data Analytics• Requires processing

of any type of data • Allow use of custom

algorithms• Scale to any size and

be efficient

Status Quo:SQL for Big Data

Declarativity does scaling and parallelization for you

Extensibility is bolted on and not “native” hard to work with anything other

than structured data difficult to extend with custom

code

Status Quo:Programming Languages for Big Data

Extensibility through custom code is “native”

Declarativity is bolted on and not “native” User often has to

care about scale and performance

SQL is 2nd class within string Often no code reuse/

sharing across queries

Why U-SQL? Declarativity and Extensibility are equally native to the language!

Get benefits of both!Makes it easy for you by unifying:• Unstructured and structured data

processing• Declarative SQL and custom imperative

Code (C#)• Local and remote Queries• Increase productivity and agility from Day

1 and at Day 100 for YOU!

The origins of U-SQL

U-SQLSCOPE

Hive

T-SQL/ ANSI SQL

SCOPE – Microsoft’s internal Big Data language• SQL and C# integration model• Optimization and Scaling model• Runs 100’000s of jobs daily

Hive• Complex data types (Maps, Arrays)• Data format alignment for text files

T-SQL/ANSI SQL• Many of the SQL capabilities (windowing functions,

meta data model etc.)

Query data where it livesEasily query data in multiple Azure data stores without moving it to a single store

Benefits• Avoid moving large amounts of data across the

network between stores• Single view of data irrespective of physical

location • Minimize data proliferation issues caused by

maintaining multiple copies• Single query language for all data• Each data store maintains its own sovereignty• Design choices based on the need• Push SQL expressions to remote SQL sources

• Projections• Filters• Joins

U-SQL Query

Query

Query

Query

WriteAzure Storage Blobs

Azure SQL in VMs

Azure SQL DB

Azure Data Lake Analytics

Query

Azure SQL Data Warehouse

Que r

y

Writ

e

Azure Data Lake Storage

Show me U-SQL!https://github.com/Azure/usql/tree/master/Examples/TweetAnalysis

• Schema on Read• Write to File• Built-in and custom

Extractors and Outputters• ADL Storage and Azure Blob

Storage

“Unstructured” Files EXTRACT Expression@s = EXTRACT a string, b int FROM "filepath/file.csv"USING Extractors.Csv(encoding: Encoding.Unicode);

• Built-in Extractors: Csv, Tsv, Text with lots of options• Custom Extractors: e.g., JSON, XML, etc.

OUTPUT ExpressionOUTPUT @sTO "filepath/file.csv"USING Outputters.Csv();

• Built-in Outputters: Csv, Tsv, Text• Custom Outputters: e.g., JSON, XML, etc. (see http://usql.io)

Filepath URIs• Relative URI to default ADL Storage account: "filepath/file.csv"

• Absolute URIs:• ADLS:

"adl://account.azuredatalakestore.net/filepath/file.csv"• WASB: "wasb://container@account/filepath/file.csv"

U-SQL extensibilityExtend U-SQL with C#/.NET

Built-in operators, function, aggregates

C# expressions (in SELECT expressions)

User-defined aggregates (UDAGGs)

User-defined functions (UDFs)

User-defined operators (UDOs)

Extending U-SQL!https://github.com/Azure/usql/tree/master/Examples/TweetAnalysis

Managing Assemblies

• CREATE ASSEMBLY db.assembly FROM @path;• CREATE ASSEMBLY db.assembly FROM byte[];

• Can also include additional resource files

• REFERENCE ASSEMBLY db.assembly;

• Referencing .Net Framework Assemblies• Always accessible system namespaces:

• U-SQL specific (e.g., for SQL.MAP)• All provided by system.dll system.core.dll

system.data.dll, System.Runtime.Serialization.dll, mscorelib.dll (e.g., System.Text, System.Text.RegularExpressions, System.Linq)

• Add all other .Net Framework Assemblies with:REFERENCE SYSTEM ASSEMBLY [System.XML];

• Enumerating Assemblies• Powershell command• U-SQL Studio Server Explorer

• DROP ASSEMBLY db.assembly;

Create assemblies Reference assemblies Enumerate assemblies Drop assemblies

VisualStudio makes registration easy!

USING clause 'USING' csharp_namespace | Alias '=' csharp_namespace_or_class.

Examples: DECLARE @ input string = "somejsonfile.json";

REFERENCE ASSEMBLY [Newtonsoft.Json];REFERENCE ASSEMBLY [Microsoft.Analytics.Samples.Formats];

USING Microsoft.Analytics.Samples.Formats.Json;

@data0 = EXTRACT IPAddresses string FROM @input USING new JsonExtractor("Devices[*]");

USING json = [Microsoft.Analytics.Samples.Formats.Json.JsonExtractor];

@data1 = EXTRACT IPAddresses string FROM @input USING new json("Devices[*]");

Allows shortening and disambiguating C# namespace and class names

Show me File Sets!https://github.com/Azure/usql/tree/master/Examples/TweetAnalysis

• Simple Patterns• Virtual Columns• Only on EXTRACT for now

(On OUTPUT being worked on)

File Sets Simple pattern language on filename and path@pattern string = "/input/{date:yyyy}/{date:MM}/{date:dd}/{*}.{suffix}";

• Binds two columns date and suffix• Wildcards the filename• Limits on number of files

(Current limit 800 and 3000 being increased in next refresh)

Virtual columnsEXTRACT

name string, suffix string // virtual column, date DateTime // virtual column

FROM @patternUSING Extractors.Csv();

• Refer to virtual columns in query predicates to get partition elimination(otherwise you will get a warning)

Create shareable data and codehttps://github.com/Azure/usql/tree/master/Examples/TweetAnalysis

Meta Data Object ModelADLA Account/Catalog

Database

Schema

[1,n]

[1,n]

[0,n]

tables views TVFs

C# Fns C# UDAgg

ClusteredIndex

partitions

C# Assemblies

C# Extractors

Data Source

C# ReducersC# Processors

C# CombinersC# Outputters

Ext. tables

Abstract objects

User objects

Refers toContains Implemented and named by

Procedures

Creden-tials

MD Name C# Name

C# Applier

Table Types

Legend

Statistics

C# UDTs

• Naming• Discovery• Sharing• Securing

U-SQL Catalog Naming• Default Database and Schema context: master.dbo• Quote identifiers with []: [my table]• Stores data in ADL Storage /catalog folder

Discovery• Visual Studio Server Explorer• Azure Data Lake Analytics Portal• SDKs and Azure Powershell commands

Sharing• Within an Azure Data Lake Analytics account

Securing• Secured with AAD principals at catalog level (inherited

from ADL Storage)• At General Availability: Database level access control

• CREATE TABLE• CREATE TABLE AS SELECT

Tables CREATE TABLE T (col1 int , col2 string , col3 SQL.MAP<string,string> , INDEX idx CLUSTERED (col1 ASC) DISTRIBUTED BY HASH (driver_id) );

• Structured Data• Built-in Data types only (no UDTs)• Clustered Index (needs to be specified): row-oriented• Fine-grained distribution (needs to be specified):

• HASH, DIRECT HASH, RANGE, ROUND ROBIN

CREATE TABLE T (INDEX idx CLUSTERED …) AS SELECT …;CREATE TABLE T (INDEX idx CLUSTERED …) AS EXTRACT…;CREATE TABLE T (INDEX idx CLUSTERED …) AS myTVF(DEFAULT);

• Infer the schema from the query• Still requires index and partitioning

Let’s do some SQL with U-SQL!https://github.com/Azure/usql/tree/master/Examples/TweetAnalysis

U-SQLJoins

Join operators

• INNER JOIN• LEFT or RIGHT or FULL OUTER JOIN• CROSS JOIN• SEMIJOIN

• equivalent to IN subquery• ANTISEMIJOIN

• Equivalent to NOT IN subqueryNotes

• ON clause comparisons need to be of the simple form: rowset.column == rowset.columnor AND conjunctions of the simple equality comparison

• If a comparand is not a column, wrap it into a column in a previous SELECT

• If the comparison operation is not ==, put it into the WHERE clause

• turn the join into a CROSS JOIN if no equality comparison

Reason: Syntax calls out which joins are efficient

U-SQLAnalytics

Windowing Expression

Window_Function_Call 'OVER' '(' [ Over_Partition_By_Clause ]

[ Order_By_Clause ] [ Row _Clause ]')'.

Window_Function_Call :=Aggregate_Function_Call

| Analytic_Function_Call| Ranking_Function_Call.

Windowing Aggregate Functions

ANY_VALUE, AVG, COUNT, MAX, MIN, SUM, STDEV, STDEVP, VAR, VARP

Analytics Functions

CUME_DIST, FIRST_VALUE, LAST_VALUE, PERCENTILE_CONT, PERCENTILE_DISC, PERCENT_RANK; soon: LEAD/LAG

Ranking Functions

DENSE_RANK, NTILE, RANK, ROW_NUMBER

“Top 5”sSurprises for SQL Users

• AS is not as• C# keywords and SQL keywords overlap• Costly to make case-insensitive -> Better

build capabilities than tinker with syntax• = != ==

• Remember: C# expression language• null IS NOT NULL

• C# nulls are two-valued• PROCEDURES but no WHILE• No UPDATE nor MERGE

Summary of U-SQL

U-SQL Language Philosophy

Declarative Query and Transformation Language:• Uses SQL’s SELECT FROM WHERE with GROUP

BY/Aggregation, Joins, SQL Analytics functions• Optimizable, ScalableExpression-flow programming style:• Easy to use functional lambda composition • Composable, globally optimizableOperates on Unstructured & Structured Data• Schema on read over files• Relational metadata objects (e.g. database, table)Extensible from ground up:• Type system is based on C#• Expression language IS C#• User-defined functions (U-SQL and C#)• User-defined Aggregators (C#)• User-defined Operators (UDO) (C#)

U-SQL provides the Parallelization and Scale-out Framework for Usercode• EXTRACTOR, OUTPUTTER, PROCESSOR, REDUCER,

COMBINER, APPLIERFederated query across distributed data sources

REFERENCE MyDB.MyAssembly;

CREATE TABLE T( cid int, first_order DateTime , last_order DateTime, order_count int , order_amount float );

@o = EXTRACT oid int, cid int, odate DateTime, amount float FROM "/input/orders.txt" USING Extractors.Csv();

@c = EXTRACT cid int, name string, city string FROM "/input/customers.txt" USING Extractors.Csv();

@j = SELECT c.cid, MIN(o.odate) AS firstorder , MAX(o.date) AS lastorder, COUNT(o.oid) AS ordercnt , AGG<MyAgg.MySum>(c.amount) AS totalamount FROM @c AS c LEFT OUTER JOIN @o AS o ON c.cid == o.cid WHERE c.city.StartsWith("New") && MyNamespace.MyFunction(o.odate) > 10 GROUP BY c.cid;

OUTPUT @j TO "/output/result.txt"USING new MyData.Write();

INSERT INTO T SELECT * FROM @j;

Unifies natively SQL’s declarativity and C#’s extensibilityUnifies querying structured and unstructuredUnifies local and remote queriesIncrease productivity and agility from Day 1 forward for YOU!Sign up for an Azure Data Lake account and join the Public Preview http://www.azure.com/datalake and give us your feedback via http://aka.ms/adlfeedback or at http://aka.ms/u-sql-survey!

This is why U-SQL!

Additional Resources Blogs and community page:

http://usql.io (U-SQL Github) http://blogs.msdn.microsoft.com/azuredatalake/ http://blogs.msdn.microsoft.com/mrys/ https://channel9.msdn.com/Search?term=U-SQL#ch9Se

arch

Documentation and articles: http://aka.ms/usql_reference https://azure.microsoft.com/en-us/documentation/servic

es/data-lake-analytics/ https://msdn.microsoft.com/en-us/magazine/mt614251

ADL forums and feedback http://aka.ms/adlfeedback https://social.msdn.microsoft.com/Forums/azure/en-US/h

ome?forum=AzureDataLake

http://stackoverflow.com/questions/tagged/u-sql

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