Are you over 18 and want to see adult content?
More Annotations
A complete backup of https://www.kaufmich.com/Deutsche-tanja
Are you over 18 and want to see adult content?
A complete backup of https://esfacil-ganar-asi-si-sabes-como.blogspot.com/
Are you over 18 and want to see adult content?
A complete backup of https://nvanthyn.blogspot.com/
Are you over 18 and want to see adult content?
A complete backup of https://dnsdblookup.com/stboy.net/
Are you over 18 and want to see adult content?
A complete backup of https://en.wikipedia.org/wiki/Thor:_The_Dark_World
Are you over 18 and want to see adult content?
A complete backup of https://us.napster.com/artist/download
Are you over 18 and want to see adult content?
Favourite Annotations
A complete backup of okyanuskoleji.k12.tr
Are you over 18 and want to see adult content?
A complete backup of tamosim.blogspot.com
Are you over 18 and want to see adult content?
A complete backup of rotsautomobielen.nl
Are you over 18 and want to see adult content?
A complete backup of thecookiesroom.com
Are you over 18 and want to see adult content?
A complete backup of objectiflune.com
Are you over 18 and want to see adult content?
A complete backup of metromatinee.com
Are you over 18 and want to see adult content?
Text
DOTNINE
Switching blog website. For quite some years now I have been active on my blog over at www.dotnine.net. While there was nothing wrong with blogging through that URL I frequently got some feedback that my blog posts were difficult to find. People don’t directly associate DotNine with SQL Server, analytics or my name. USING AZURE MACHINE LEARNING WITH AN ON-PREMISES QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load. A TOUR OF THE TRANSACTION LOG: PART 1 INSERT OPERATIONS The transaction log is a very important part of SQL Server. Every data modification operation is logged in the transaction log before being ‘hardened’ to the database file. HOW SQL SERVER STATISTICS ARE GENERATED AND UPDATED One of the easiest ways to increase query performance on your database is making sure your statistics are up-to-date. Statistics are – if you enabled the options in your database properties – automatically created and updated by the SQL Server Engine. OPTIMIZE FOR AD-HOC WORKLOADS SQL Server 2008 introduced a new advanced option called “Optimize for ad-hoc workloads”. According to Microsoft: The optimize for ad hoc workloads option is used to improve the efficiency of the plan cache for workloads that contain many single use ad hoc batches.When this option is set to 1, the Database Engine stores a small compiled plan stub in the plan cache when a batch is compiled QUERY STORE CUSTOM SSMS PERFORMANCE DASHBOARD The dashboard looks cool and it is very useful, but it seems that you have a bug in the two top 10 queries. I was getting no results from these on my DB, until I figured out that qsqt.query_text_id should be joined with qsq.query_text_id, instead of qsp.query_id. PERFORMING IN-DATABASE PREDICTIONS IN SQL SERVER 2016 Performing in-database predictions in SQL Server 2016 & 2017 – DotNine. Starting from SQL Server 2016 Microsoft put a lot of effort into integrating various languages used in machine learning and statistical analysis inside their database engine. In SQL Server 2016 Microsoft introduced the integration of the R language and in SQLServer 2017
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice. WAIT STATISTICS INTEGRATION INSIDE THE QUERY STORE IN SQL I remember writing an article about Query specific wait statistics being available inside execution plans in SQL Server 2016 SP1. The way that works is when you view the actual execution plan of a query (through SSMS or the XML) you are able to see the wait information that specific query ran into during execution.DOTNINE
Switching blog website. For quite some years now I have been active on my blog over at www.dotnine.net. While there was nothing wrong with blogging through that URL I frequently got some feedback that my blog posts were difficult to find. People don’t directly associate DotNine with SQL Server, analytics or my name. USING AZURE MACHINE LEARNING WITH AN ON-PREMISES QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load. A TOUR OF THE TRANSACTION LOG: PART 1 INSERT OPERATIONS The transaction log is a very important part of SQL Server. Every data modification operation is logged in the transaction log before being ‘hardened’ to the database file. HOW SQL SERVER STATISTICS ARE GENERATED AND UPDATED One of the easiest ways to increase query performance on your database is making sure your statistics are up-to-date. Statistics are – if you enabled the options in your database properties – automatically created and updated by the SQL Server Engine. OPTIMIZE FOR AD-HOC WORKLOADS SQL Server 2008 introduced a new advanced option called “Optimize for ad-hoc workloads”. According to Microsoft: The optimize for ad hoc workloads option is used to improve the efficiency of the plan cache for workloads that contain many single use ad hoc batches.When this option is set to 1, the Database Engine stores a small compiled plan stub in the plan cache when a batch is compiled QUERY STORE CUSTOM SSMS PERFORMANCE DASHBOARD The dashboard looks cool and it is very useful, but it seems that you have a bug in the two top 10 queries. I was getting no results from these on my DB, until I figured out that qsqt.query_text_id should be joined with qsq.query_text_id, instead of qsp.query_id. PERFORMING IN-DATABASE PREDICTIONS IN SQL SERVER 2016 Performing in-database predictions in SQL Server 2016 & 2017 – DotNine. Starting from SQL Server 2016 Microsoft put a lot of effort into integrating various languages used in machine learning and statistical analysis inside their database engine. In SQL Server 2016 Microsoft introduced the integration of the R language and in SQLServer 2017
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice. WAIT STATISTICS INTEGRATION INSIDE THE QUERY STORE IN SQL I remember writing an article about Query specific wait statistics being available inside execution plans in SQL Server 2016 SP1. The way that works is when you view the actual execution plan of a query (through SSMS or the XML) you are able to see the wait information that specific query ran into during execution. QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load. CUSTOM QUERY STORE PERFORMANCE DASHBOARD Download the QueryStoreDashboard.zip file using the button at the bottom of this page, unzip the .zip file and save the .rdl at a convenient location. Start op SQL Server Management Studio and connect to the instance were you want to use the dashboard. Browse to the directory where you saved the QueryStoreDashboard.rdl file and select“Open”.
OPTIMIZE FOR AD-HOC WORKLOADS SQL Server 2008 introduced a new advanced option called “Optimize for ad-hoc workloads”. According to Microsoft: The optimize for ad hoc workloads option is used to improve the efficiency of the plan cache for workloads that contain many single use ad hoc batches.When this option is set to 1, the Database Engine stores a small compiled plan stub in the plan cache when a batch is compiled AZURE MACHINE LEARNING ALGORITHM FLOWCHART The Azure Machine Learning Algorithm Flowchart guides you to an algorithm based on questions, just follow the green (positive answer) or red (negative answer) arrows! At every algorithm a rating is displayed for three properties: training time, accuracy and customization options. The more stars, the better the algorithmperforms for that
IN-MEMORY OLTP PART 2 : MEMORY-OPTIMIZED TABLES In part 1 of the In-memory OLTP articles we gave you an introduction into In-memory OLTP, showing what the requirements are, the limitations and a quick look at the Advisors.. In this article we are going to dive a little deeper into a large portion of In-memory OLTP: Memory-Optimized (or In-memory) tables! A large part of the performance increase in In-memory OLTP comes from these Memory REPLAY YOUR WORKLOAD THROUGH THE QUERY STORE In a nutshell: Query Store Replay is a free, open-source, Powershell based script that extracts queries through the Query Store of one database, and replays them to another database, on another server if you so wish. The main advantage of using the Query Store Replay script is that you can extract and replay your (production) workload onCRAZY DATA SCIENCE
Crazy Data Science is a YouTube channel I created to show off real-world Data Science methods and techniques applied to “interesting” problems. And with interesting I mean cases where you wouldn’t normally expect Data Science. To kick off the channel I uploaded the first video Slayer Analytics that dives into some statistical exploration INDEX FRAGMENTATION AND WHY YOU SHOULD CARE REORGANIZE should be used when index fragmentation is between 5 and 30% (Microsoft guidelines) and it basicly reorders your index to remove the white spaces and create a continous chain of pages. ALTER INDEX . REBUILD creates a new index and drops the old one. Microsoft suggests using this option if your index fragmentation is greater then30%.
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice. SQL SERVER 2016 SP1 QUERY SPECIFIC WAIT STATISTICS You can view the Wait Statistics information stored inside the execution plan of a query by first enabling the “Include Actual Execution Plan” option inside SQL Server Management Studio and then executing the query. After query execution switch to the execution plan, right-click the first operator on the left and select“Properties”.
DOTNINE
Switching blog website. For quite some years now I have been active on my blog over at www.dotnine.net. While there was nothing wrong with blogging through that URL I frequently got some feedback that my blog posts were difficult to find. People don’t directly associate DotNine with SQL Server, analytics or my name. USING AZURE MACHINE LEARNING WITH AN ON-PREMISES HOW SQL SERVER STATISTICS ARE GENERATED AND UPDATED One of the easiest ways to increase query performance on your database is making sure your statistics are up-to-date. Statistics are – if you enabled the options in your database properties – automatically created and updated by the SQL Server Engine. QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load. A TOUR OF THE TRANSACTION LOG: PART 1 INSERT OPERATIONS The transaction log is a very important part of SQL Server. Every data modification operation is logged in the transaction log before being ‘hardened’ to the database file.CRAZY DATA SCIENCE
Crazy Data Science is a YouTube channel I created to show off real-world Data Science methods and techniques applied to “interesting” problems. And with interesting I mean cases where you wouldn’t normally expect Data Science. To kick off the channel I uploaded the first video Slayer Analytics that dives into some statistical exploration QUERY STORE CUSTOM SSMS PERFORMANCE DASHBOARD The dashboard looks cool and it is very useful, but it seems that you have a bug in the two top 10 queries. I was getting no results from these on my DB, until I figured out that qsqt.query_text_id should be joined with qsq.query_text_id, instead of qsp.query_id. PERFORMING IN-DATABASE PREDICTIONS IN SQL SERVER 2016 Performing in-database predictions in SQL Server 2016 & 2017 – DotNine. Starting from SQL Server 2016 Microsoft put a lot of effort into integrating various languages used in machine learning and statistical analysis inside their database engine. In SQL Server 2016 Microsoft introduced the integration of the R language and in SQLServer 2017
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice. SP_WHATSUPQUERYSTORE sp_WhatsupQueryStore is a Stored Procedure that retrieves all kinds of information from a Query Store enabled database. sp_WhatsupQueryStore is easily configurable and can return a wide variety of Query Store information like: Queries with forced execution plans. Query Store configuration. Top n queries based on Duration/CPU/IO and nr. ofDOTNINE
Switching blog website. For quite some years now I have been active on my blog over at www.dotnine.net. While there was nothing wrong with blogging through that URL I frequently got some feedback that my blog posts were difficult to find. People don’t directly associate DotNine with SQL Server, analytics or my name. USING AZURE MACHINE LEARNING WITH AN ON-PREMISES HOW SQL SERVER STATISTICS ARE GENERATED AND UPDATED One of the easiest ways to increase query performance on your database is making sure your statistics are up-to-date. Statistics are – if you enabled the options in your database properties – automatically created and updated by the SQL Server Engine. QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load. A TOUR OF THE TRANSACTION LOG: PART 1 INSERT OPERATIONS The transaction log is a very important part of SQL Server. Every data modification operation is logged in the transaction log before being ‘hardened’ to the database file.CRAZY DATA SCIENCE
Crazy Data Science is a YouTube channel I created to show off real-world Data Science methods and techniques applied to “interesting” problems. And with interesting I mean cases where you wouldn’t normally expect Data Science. To kick off the channel I uploaded the first video Slayer Analytics that dives into some statistical exploration QUERY STORE CUSTOM SSMS PERFORMANCE DASHBOARD The dashboard looks cool and it is very useful, but it seems that you have a bug in the two top 10 queries. I was getting no results from these on my DB, until I figured out that qsqt.query_text_id should be joined with qsq.query_text_id, instead of qsp.query_id. PERFORMING IN-DATABASE PREDICTIONS IN SQL SERVER 2016 Performing in-database predictions in SQL Server 2016 & 2017 – DotNine. Starting from SQL Server 2016 Microsoft put a lot of effort into integrating various languages used in machine learning and statistical analysis inside their database engine. In SQL Server 2016 Microsoft introduced the integration of the R language and in SQLServer 2017
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice. SP_WHATSUPQUERYSTORE sp_WhatsupQueryStore is a Stored Procedure that retrieves all kinds of information from a Query Store enabled database. sp_WhatsupQueryStore is easily configurable and can return a wide variety of Query Store information like: Queries with forced execution plans. Query Store configuration. Top n queries based on Duration/CPU/IO and nr. of QUERY STORE INSTANCE DASHBOARD The second section of the Query Store Instance Dashboard digs deeper into the runtime metrics stored in the Query Store. Here you can see graphs that detail CPU Time, Nr. Of plan executions and logical reads/writes all shown per-database and including a Total so you can easily see which database is responsible for the total instance load.CRAZY DATA SCIENCE
Crazy Data Science is a YouTube channel I created to show off real-world Data Science methods and techniques applied to “interesting” problems. And with interesting I mean cases where you wouldn’t normally expect Data Science. To kick off the channel I uploaded the first video Slayer Analytics that dives into some statistical exploration IN-MEMORY OLTP PART 2 : MEMORY-OPTIMIZED TABLES In part 1 of the In-memory OLTP articles we gave you an introduction into In-memory OLTP, showing what the requirements are, the limitations and a quick look at the Advisors.. In this article we are going to dive a little deeper into a large portion of In-memory OLTP: Memory-Optimized (or In-memory) tables! A large part of the performance increase in In-memory OLTP comes from these Memory AZURE MACHINE LEARNING ALGORITHM FLOWCHART The Azure Machine Learning Algorithm Flowchart guides you to an algorithm based on questions, just follow the green (positive answer) or red (negative answer) arrows! At every algorithm a rating is displayed for three properties: training time, accuracy and customization options. The more stars, the better the algorithmperforms for that
OPTIMIZE FOR AD-HOC WORKLOADS SQL Server 2008 introduced a new advanced option called “Optimize for ad-hoc workloads”. According to Microsoft: The optimize for ad hoc workloads option is used to improve the efficiency of the plan cache for workloads that contain many single use ad hoc batches.When this option is set to 1, the Database Engine stores a small compiled plan stub in the plan cache when a batch is compiled REPLAY YOUR WORKLOAD THROUGH THE QUERY STORE In a nutshell: Query Store Replay is a free, open-source, Powershell based script that extracts queries through the Query Store of one database, and replays them to another database, on another server if you so wish. The main advantage of using the Query Store Replay script is that you can extract and replay your (production) workload on EXAMINING OLEDB WAITS On our adventure through the various types of wait statistics we end up at another popular wait type: OLEDB. In this article we will take a closer look at OLEDB waits to help you understand where they come from. OLEDB. OLEDB or, Object Linking and Embedding DataBase, is CUSTOM QUERY STORE PERFORMANCE DASHBOARD Download the QueryStoreDashboard.zip file using the button at the bottom of this page, unzip the .zip file and save the .rdl at a convenient location. Start op SQL Server Management Studio and connect to the instance were you want to use the dashboard. Browse to the directory where you saved the QueryStoreDashboard.rdl file and select“Open”.
INDEX FRAGMENTATION AND WHY YOU SHOULD CARE REORGANIZE should be used when index fragmentation is between 5 and 30% (Microsoft guidelines) and it basicly reorders your index to remove the white spaces and create a continous chain of pages. ALTER INDEX . REBUILD creates a new index and drops the old one. Microsoft suggests using this option if your index fragmentation is greater then30%.
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SQL Server configuration. The first thing I would like to point out here is that you will need to run SQL Server 2016 or 2017 with in-database R services enabled if you plan to recreate the examples. The reason for this is that we will be using the sp_execute_external_script procedure to execute R code that will access the AzureML webservice.DOTNINE
SQL Server and Advanced Analytics Toggle search __ Toggle navigation__
Search for:
* Home
* About
* Blog
* Video’s
Home »
14
Nov 2018
SWITCHING BLOG WEBSITE__Enrico
__General
__4 comments
For quite some years now I have been active on my blog over at www.dotnine.net. While there was nothing wrong with blogging through that URL I frequently got some feedback that my blog posts were difficult to find. People don’t directly associate DotNine with SQL Server, analytics or my name. So to fix that problem IRead More __
31
Oct 2018
SPEAKING AT PASS SUMMIT__Enrico
__Events
__No comments yet
The title says it all, this year I have been selected as a speaker at the world’s largest Microsoft Data Platform conference: PASS Summit! I will be presenting on one of my favourite topics: In-database analytics inside Microsoft SQL Server (www.pass.org/summit/2018/sessions/details.aspx?sid=76976). So if you happen to be at PASS Summit and want to learn moreRead More __
13
Mar 2018
CRAZY DATA SCIENCE
__Enrico
__Crazy Data Science__29 comments
I am pretty hyped to be able to finally announce a new project of mine that I have been working on for quite some time now: Crazy Data Science! Crazy Data Science is a YouTube channel I created to show off real-world Data Science methods and techniques applied to “interesting” problems. And with interesting I mean casesRead More __
11
Dec 2017
ACCESSING AZUREML MODELS THROUGH SQL SERVER IN-DATABASE R SERVICES__Enrico
__Azure Machine Learning, In-database
analytics
__12 comments
In a previous article I discussed the various methods available in SQL Server 2016 & 2017 to perform in-database analytics. In the article I used a model that was stored directly inside SQL Server to perform predictions. But what if your models are not stored inside SQL Server but are build inside Azure Machine Learning?Read More __
17
Oct 2017
PERFORMING IN-DATABASE PREDICTIONS IN SQL SERVER 2016 & 2017__Enrico
__In-database analytics__8 comments
Starting from SQL Server 2016 Microsoft put a lot of effort into integrating various languages used in machine learning and statistical analysis inside their database engine. In SQL Server 2016 Microsoft introduced the integration of the R language and in SQL Server 2017 Python was added. Both these languages give you the advantages ofbringing
Read More __
21
Jul 2017
AZURE MACHINE LEARNING ALGORITHM FLOWCHART__Enrico
__Azure Machine Learning__4 comments
When you are working with Machine Learning there are many things you need to keep an eye on. You need to prepare the data, deal with any missing values and you need to select an algorithm you will be using for you model. Choosing an algorithm can be a difficult one though. Azure Machine LearningRead More __
14
May 2017
USING AZURE MACHINE LEARNING WITH AN ON-PREMISES DATABASE__Enrico
__Azure Machine Learning__27 comments
With Azure Machine Learning (AzureML) you have access to a cloud based, flexible and friendly method to perform machine learning tasks on your data. One disadvantage I frequently run into is that cloud based approach of AzureML since the data you are building your machine learning models on has to be in the cloud asRead More __
05
May 2017
GROUPBY CONFERENCE RECORDING OF INTRODUCING THE SQL SERVER 2016 QUERY STORE AVAILABLE NOW!__Enrico
__Events
__6 comments
Good news! The recording of my session “Introducing the SQL Server 2016 Query Store” at the GroupBy conference 2 weeks ago is available for your viewing, listening and reading pleasure! //groupby.org/2017/05/introducing-the-sql-server-2016-query-store/ Not only is a video recording available at the page above, but also a podcast version if you prefer only audio and a transcriptRead More __
23
Apr 2017
WAIT STATISTICS INTEGRATION INSIDE THE QUERY STORE IN SQL SERVER VNEXT__Enrico
__Query Store , Wait Stats__2 comments
I remember writing an article about Query specific wait statistics being available inside execution plans in SQL Server 2016 SP1. The way that works is when you view the actual execution plan of a query (through SSMS or the XML) you are able to see the wait information that specific query ran into during execution.Read More __
27
Feb 2017
CONFIGURING AND ANALYZING THE QUERY STORE THROUGH DBATOOLS__Enrico
__Query Store
__8 comments
In case you didn’t know this already, dbatools is an awesome collection of Powershell functions that will help you immensely in your work as a DBA. Just one example: migrating SQL Server Instances takes a massive amount of work. You need to backup and restore every database, write down instance specific configuration and apply itRead More __
1 2 3 … 7
ABOUT
Enrico van de Laar is crazy for everything that deals with data in the Microsoft stack. His specialties are SQL Server and Advanced Analytics. Enrico is a Microsoft Data Platform MVP, an author and he frequently speaks on various conferences across the globe.SOCIAL
*
*
*
CATEGORIES
* Azure Machine Learning* Backup/Restore
* Books
* Crazy Data Science* Events
* From DBA to Data Science* General
* In-database analytics* In-Memory OLTP
* Indexing
* Internals
* Query Store
* Quick Tips
* SQL Server Management Studio* Uncategorized
* Wait Stats
ARCHIVES
* November 2018
* October 2018
* March 2018
* December 2017
* October 2017
* July 2017
* May 2017
* April 2017
* February 2017
* December 2016
* November 2016
* September 2016
* June 2016
* April 2016
* March 2016
* September 2015
* August 2015
* July 2015
* May 2015
* April 2015
* March 2015
* January 2015
* November 2014
* September 2014
* August 2014
* July 2014
* June 2014
* May 2014
* April 2014
* March 2014
* February 2014
* January 2014
* November 2013
* September 2013
* August 2013
* June 2013
* May 2013
* April 2013
* February 2013
__
Powered by WordPress . Designed by MageeWP Themes.
Details
Copyright © 2024 ArchiveBay.com. All rights reserved. Terms of Use | Privacy Policy | DMCA | 2021 | Feedback | Advertising | RSS 2.0