Tag: "sqlbits"
Konferenzen im SQL Server Sommer 2016 – Conferences in SQL Server summer 2016
May 17th
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(DE) Hinweis: in den 3 Wochen seit Freischaltung der Anmeldung sind bereits 70% der Plätze vergeben worden. Wer sich noch einen Platz sichern möchte aber nicht weiß, wie schnell seine Einkaufsabteilung es schafft, kann sich gern an mich direkt wenden. |
(EN) Note: in the 2 weeks since activation of registration already 70% of the places have already been filled. If you want to secure a spot but don’t know how you’re your purchase department will make it, you are welcome to contact me directly. |
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Davor noch aber findet, wie die beiden Jahre zuvor, der deutsche SQLSaturday „Rheinland“ in der Hochschule St. Augustin bei Bonn statt. |
But before, the German SQLSaturday „Rheinland“ is taking place, like the previous two years. |
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Ich selber werde auch mit einem Vortrag vertreten sein. Diesmal mit einem Beitrag zu ganz klassischer Performance Tracing. Allerdings nicht, wie man immer noch hin und wieder „in the wild“ sieht mit SQL Profiler, sondern natürlich mit aktuellen Technologien wie Extended Events und sogar der neuen Query Store von SQL Server 2016: |
I will also be presenting. This time, it is going to be on the entirely classical topic of Performance Tracing. However, not with SQL Profiler as can be seen once in a while “in the wild,” but of course with current technologies such as Extended Events and even the new Query Store by SQL Server 2016: |
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Analysieren von SQL Server Workloads mit DMVs und XEvents Diese Session führt durch eine beispielhafte Performance-Analyse unter der Verwendung von DMVs und Extended Events. Wir sehen, wie man eine Top-Down Analyse mit eingebauten Tools durchführen kann und wie man eine feingradige Analyse selbst mittels den „Wait Statistics“ durchführen kann, um Performance-Problemen und Bottlenecks auf die Schliche zu kommen. Zur Identifizierung von Plan-Änderungen wird auch die neue Query Data Store von SQL Server 2016 zum Einsatz kommen. Wer auf dem Feld der Performance-Analysen noch neu ist oder sehen möchte, wie man an die Herausforderung herangehen kann, wird hier praktische Einblicke erhalten, wie man eine Workload analysieren kann. – Die Session ist selbstverständlich „Profiler-free“ ;-) |
Performance Analyzing SQL Server workloads with DMVs and XEvents This session you will be lead you through an example performance-analysis using mainly DMVs and Extended Events. You will see how a top-down analysis using built-in tools can be conducted. This will include wait statistics on different scopes to identify performance problems and bottlenecks up to identifying query plan changes – with & without using the Query Store of SQL Server 2016. If you are new to performance analyzing this session will give you a practical insight into how to methodically approach performance troubleshooting.
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Asien Im August bin ich wieder in Asien unterwegs und das zweite Mal in Folge auf der größten SQL Server Konferenz Asiens: dem SQL Server Geeks Summit in Bangalore, Indien. |
Asia In August, I will be traveling Asia again and attending the largest SQL Server Conference in Asia for the second time in a row: the SQL Server Geeks Summit in Bangalore, India. |
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Dort werde ich dieses Jahr eine ganztägige Pre-Con geben. Thema: Die In-Memory Storage Engines von SQL Server, die mit dem SQL Server 2016 umfangreich verbessert worden. Das heißt es geht um ColumnStore, Memory Optimized Tabellen, Memory Optimized Indexe, und die Kobinationsmöglichkeiten mit traditioneller Row-Store oder auch ColumnStore für Mixed OLAP als auch OLTP workloads. |
This time, I will be giving a full-day Pre-Con. Topic: The In-Memory Storage Engine of SQL Server that have been extensively improved with SQL Server 2016. That is, it will be about ColumnStore, Memory Optimized Tables, Memory Optimized Indexes, and the combination possibilities with traditional Row-Store or also ColumnStore for Mixed OLAP as well as OLTP workloads. |
Pre-Con Title:
The Present and Future: In-Memory in SQL Server – from 0 to Operational Analytics Master
Track: DBA/DEV
Pre-Con Abstract:
When the Columnstore Index technology, based on the xVelocity In-Memory engine, came with SQL Server 2012 in the form of Nonclustered Columnstore, and SQL Server 2014 brought us updatable Clustered Columnstore Indexes plus a completely new In-Memory OLTP Engine, “XTP”, for memory optimized table & indexes, those features were still new and because of their limitations used only rarely.
SQL Server 2016 takes both technology onto a whole new level:
Columnstore indexes among other things now support snapshot isolation and hence fully support readable secondaries. Batch execution is not exclusively for parallel threaded queries anymore. They can be combined with other B-tree indexes and even be filtered and support referential integrity with primary and foreign key constraints. Also so-called In-Memory Operational Analytics is supported by the ability to create Columnstore Indexes on memory optimized tables.
On the other hand the In-Memory engine has been extensively improved in terms of both scalability and T-SQL language support, taking away many of the relevant limitations for adaption of version 1 in a similar way than the Columnstore technology. For example altering of pre-compiled objects is now possible, bucket-counts can be adjusted, natively compiled stored procedures can be recompiled and foreign keys are supported as well as encryption with TDE.
All those improvements will make In-Memory technologies a viable option in many projects. For Datawarehouses many (including me) say, that Columnstore will become the default storage type for all objects. And it can be foreseen that over the years the same will happen for OLTP-tables that have to support highly concurrent workloads will be based on memory optimized tables.
It’s time to extend our skills to those technologies to be able implement and support the new types of storage that are coming to our databases to address the fact of ever more data being stored and queried and performance demands and (real time) analytic requirements going up.
At this full-day training day, Microsoft Certified Master for the Data Platform Andreas Wolter, familiar with SQL Servers In-Memory technologies from the early bits on, will give a complete picture on the current state of technology. Attendees will learn how and where to use either In-Memory OLTP or Columnstore or even both for efficient queries and data storing and the important bits both from developers and administrators perspective.
Modules/Topics Include:
1. Columnstore Storage Engine and compression internals
2. What is the benefit for OLAP performance
3. When to use Clustered or Nonclustered Columnstore Indexes
4. XTP Engine internals for In-Memory OLTP performance benefits
5. Memory optimized Tables, indexes and Variables
6. Natively compiled stored procedures & triggers
7. Combination of Row-Store, Columnstore/xVelocity and XTP engine for operational analytics
Key Takeaways:
1. How the new storage engines Columnstore & XTP work behind the covers
2. What are the strengths and weaknesses of these alternate storage engines and how can they be played out best
3. How to get a quick start with In-Memory optimized objects in almost any environment
4. What are the typical performance patterns that these technologies address
5. How to build highly performing Datawarehouse tables
6. How to improve OLTP hotspot tables with In-Memory technologies
7. How to enable real-time analytics of operational data
8. What’s important from file management perspective for administrators
9. How can Columnstore and In-Memory Hash- & Range-indexes be maintained
10. What hotspots can you expect for those technologies – or is there any?
Demos:
1. Performance-Improvements for OLAP workloads with Nonclustered Columnstore indexes …
2. … Clustered Columnstore indexes
3. Performance-Improvements for OLTP workloads with memory optimized tables, indexes and code
4. Operational analytics on row store vs operational analytics on In-Memory
5. … all under different workload-types
6. How do Columnstore indexes handle updates to data under the covers
7. How In-Memory optimized objects look like on disk
Attendee Pre-requisites:
1. Basic T-SQL knowledge for code-reading
2. clustered vs nonclustered indexes basics
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Obendrein werde ich noch zwei normalere Sessions auf der Hauptkonferenz geben. Die Themen stehen noch nicht fest. Ich freue mich bereits wieder auf das enthusiastische Publikum in Indien! |
Added to that I will give two more normal sessions at the main conference. The topics are not final yet. I am looking forward to the enthusiastic audience in India again! |
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Nach Indien werde ich auf der SQLSaturday Singapore präsentieren. Diese Konferenz wird bei Microsoft Singapore Operations Pte Ltd, One Marina Boulevard stattfinden – inmitten der berühmtesten Sehenswürdigkeiten Singapurs. Hier gebe ich möglicherweise auch eine PreCon, aber die Planung ist noch nicht abgeschlossen, also mal schauen, was es sein wird. Auch auf dieses Event freue ich mich sehr. |
After India I will be presenting at SQLSaturday Singapore. This event will be held at Microsoft Singapore Operations Pte Ltd, One Marina Boulevard – right in the center of the most famous sights of Singapore. Also here I might give a PreCon, but the planning is not finalized yet, so let’s see what it will be. I am very much looking forward to this event as well. |
Cu in St. Augustin, Bangalore or Singapore – your turn to choose ;-)
Andreas
Speaking at SQLBits 2014: PreCon on In-Memory OLTP and Security session
May 7th
Sprecher auf der SQLBits 2014 zu In-Memory OLTP und Sicherheit
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Niko Neugebauer und ich geben am 17. Juli die ganztägige Veranstaltung „In-Memory Technologies in SQL Server 2014: CCI & XTP“. Niko wird seine Erfahrung mit den neuen Clustered ColumnStore Indexen teilen und ich werde die neue In-Memory OLTP Engine XTP detailliert vorstellen. |
Niko Neugebauer and I will be delivering the full day presentation „In-Memory Technologies in SQL Server 2014: CCI & XTP“ on July 17th. Niko will share his experience with the new Clusterd ColumnStore Indexes and I will present the all new In-Memory Engine XTP in detail. |
In this full-day session MVP Niko Neugebauer and MCM Andreas Wolter are going to take you onto a journey to In-Memory in SQL Server 2014 which contains two features of great impact on how databases perform and are designed: The improved Columnstore Indexes: Clustered, Updatable, they change the way BI & Datawarehouse Systems will be designed & used. On the OLTP other side, the XTP engine (Codename “Hekaton”) brings huge performance improvements for OLTP workloads.
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- Diesen Ganztages-Vortrag haben wir bereits in ähnlicher Form auf dem Deutschen Launch Event für den SQL Server 2014 gehalten. Das ist eine überaus große Ehre für uns, zumal dort seit Jahren einige echte Gurus ihres Fachs auftreten. So befinden wir uns dieses Jahr in der Illustren Gesellschaft von Brent Ozar, Brian Knight, Jennifer Stirrup, Dejan Sarka, Marco Russo, Adam Jorgensen und John Welch, Itzik Ben-Gan, Allan Hirt, Dave Ballantyne und David Morrison und Simon Sabin!
Am Freitag, den 18., halte ich dann meine bekannte Security Session: „“SQL Attack…ed” – SQL Server under attack: SQL Injection“. Der Samstag ist übrigens „Community day“ mit kostenloser Teilnahme – die Plätze werden wie für alle Tage aber schnell weg sein. Also nicht zu lange warten. |
- We presented this full day session already in similar shape at the German Launch Event for SQL Server 2014. This is a huge honor for us, especially since some of the real Gurus of their subject have been presenting there for years. So this year we are finding ourselves in the illustrious company of Brent Ozar, Brian Knight, Jennifer Stirrup, Dejan Sarka, Marco Russo, Adam Jorgensen and John Welch, Itzik Ben-Gan, Allan Hirt, Dave Ballantyne and David Morrison and Simon Sabin!
On Friday the 18th, I will then give my well-known Security Session: „“SQL Attack…ed” – SQL Server under attack: SQL Injection”. Saturday, by the way, is “Community day” with attendance free of charge– the seats are going to be taken quickly though, as for all days, so do not wait too long. |
Cu at SQLBits,
Andreas
