SQL Server 2016 introduces new features for business intelligence and reporting. PolyBase allows querying data across SQL Server and Hadoop using T-SQL. Integration Services has improved support for AlwaysOn availability groups and incremental package deployment. Reporting Services adds HTML5 rendering, PowerPoint export, and the ability to pin report items to Power BI dashboards. Mobile Report Publisher enables developing and publishing mobile reports.
Industry leading
Build mission-critical, intelligent apps with breakthrough scalability, performance, and availability.
Security + performance
Protect data at rest and in motion. SQL Server is the most secure database for six years running in the NIST vulnerabilities database.
End-to-end mobile BI
Transform data into actionable insights. Deliver visual reports on any device—online or offline—at one-fifth the cost of other self-service solutions.
In-database advanced analytics
Analyze data directly within your SQL Server database using R, the popular statistics language.
Consistent experiences
Whether data is in your datacenter, in your private cloud, or on Microsoft Azure, you’ll get a consistent experience.
SQL Server 2016 New Features and EnhancementsJohn Martin
SQL Server 2016 new features session that I delivered at SQL Relay 2015 at; Reading, London, Cardiff and Birmingham.
Looking at some of the new features currently slated for inclusion in the next version of Microsoft SQL Server 2016.
Demo Code can be found at: http://1drv.ms/1PC5smY
SQL Server 2016 is now in review! The newest version promises to deliver new real-time, built-in advanced analytics, advanced security technology, hybrid cloud scenarios as well as amazing rich visualizations on mobile devices.
There are many great reasons to move to SQL 2016, however if you are still working on SQL Server 2005 you may have another good motivator - the end-of-life clock of SQL 2005 is ticking down and support is about to end April 12, 2016.
In this deck we review the significant licensing changes introduced with SQL 2012. If our experience as Microsoft's Gold Certified Member has taught us anything - it is one thing. During migrations many of our clients get outright lost when trying to figure out the number of licenses they have or need. This often leads to under-deployment, and subsequently serious compliance issues with Microsoft. And yes, in some cases over-deployment means big savings back to your department.
Industry leading
Build mission-critical, intelligent apps with breakthrough scalability, performance, and availability.
Security + performance
Protect data at rest and in motion. SQL Server is the most secure database for six years running in the NIST vulnerabilities database.
End-to-end mobile BI
Transform data into actionable insights. Deliver visual reports on any device—online or offline—at one-fifth the cost of other self-service solutions.
In-database advanced analytics
Analyze data directly within your SQL Server database using R, the popular statistics language.
Consistent experiences
Whether data is in your datacenter, in your private cloud, or on Microsoft Azure, you’ll get a consistent experience.
SQL Server 2016 New Features and EnhancementsJohn Martin
SQL Server 2016 new features session that I delivered at SQL Relay 2015 at; Reading, London, Cardiff and Birmingham.
Looking at some of the new features currently slated for inclusion in the next version of Microsoft SQL Server 2016.
Demo Code can be found at: http://1drv.ms/1PC5smY
SQL Server 2016 is now in review! The newest version promises to deliver new real-time, built-in advanced analytics, advanced security technology, hybrid cloud scenarios as well as amazing rich visualizations on mobile devices.
There are many great reasons to move to SQL 2016, however if you are still working on SQL Server 2005 you may have another good motivator - the end-of-life clock of SQL 2005 is ticking down and support is about to end April 12, 2016.
In this deck we review the significant licensing changes introduced with SQL 2012. If our experience as Microsoft's Gold Certified Member has taught us anything - it is one thing. During migrations many of our clients get outright lost when trying to figure out the number of licenses they have or need. This often leads to under-deployment, and subsequently serious compliance issues with Microsoft. And yes, in some cases over-deployment means big savings back to your department.
Microsoft SQL server 2017 Level 300 technical deckGeorge Walters
This deck covers new features in SQL Server 2017, as well as carryover features from 2012 onwards. This includes high availability, columnstore, alwayson, In-memory tables, and other enterprise features.
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
Tuning SQL Server for Sharepoint 2013- What every sharepoint consultant need...serge luca
Tuning SQL Server for SharePoint what every SharePoint consultant needs to know - SharePoint Summit Vancouver - Serge Luca (SharePoint MVP) and Isabelle Van Campenhoudt(SQ Server MVP); ShareQL, Belgium
Knowing the vast majority of the content accessed via SharePoint is stored in SQL Server, and also knowing an incorrect configuration of SQL Server can have a detrimental impact on the performance of SharePoint it is important to understand the integration of these two products. Regardless of whether you have a dedicated DBA, or the SharePoint administrator is also the DBA, there are critical SQL Server configurations that can be made that will improve the performance of SharePoint. Often DBA’s are familiar with how to manage SQL Server, but may not be familiar with some nuances that SQL Server has when integrated with SharePoint. In this session we will demonstrate how some default SQL Server settings negatively impact SharePoint and what changes can be made to improve the performance of SharePoint. These changes include database file settings and SQL Server instance settings. We'll also examine how to properly install SQL Server and SharePoint so they work together as efficiently as possible. This discussion will introduce the Best Practices framework that will allow your SharePoint administrator and/or your DBA to configure SharePoint and SQL Server to provide optimal performance for your SharePoint implementation
Microsoft SQL server 2017 Level 300 technical deckGeorge Walters
This deck covers new features in SQL Server 2017, as well as carryover features from 2012 onwards. This includes high availability, columnstore, alwayson, In-memory tables, and other enterprise features.
Want to see a high-level overview of the products in the Microsoft data platform portfolio in Azure? I’ll cover products in the categories of OLTP, OLAP, data warehouse, storage, data transport, data prep, data lake, IaaS, PaaS, SMP/MPP, NoSQL, Hadoop, open source, reporting, machine learning, and AI. It’s a lot to digest but I’ll categorize the products and discuss their use cases to help you narrow down the best products for the solution you want to build.
Tuning SQL Server for Sharepoint 2013- What every sharepoint consultant need...serge luca
Tuning SQL Server for SharePoint what every SharePoint consultant needs to know - SharePoint Summit Vancouver - Serge Luca (SharePoint MVP) and Isabelle Van Campenhoudt(SQ Server MVP); ShareQL, Belgium
Knowing the vast majority of the content accessed via SharePoint is stored in SQL Server, and also knowing an incorrect configuration of SQL Server can have a detrimental impact on the performance of SharePoint it is important to understand the integration of these two products. Regardless of whether you have a dedicated DBA, or the SharePoint administrator is also the DBA, there are critical SQL Server configurations that can be made that will improve the performance of SharePoint. Often DBA’s are familiar with how to manage SQL Server, but may not be familiar with some nuances that SQL Server has when integrated with SharePoint. In this session we will demonstrate how some default SQL Server settings negatively impact SharePoint and what changes can be made to improve the performance of SharePoint. These changes include database file settings and SQL Server instance settings. We'll also examine how to properly install SQL Server and SharePoint so they work together as efficiently as possible. This discussion will introduce the Best Practices framework that will allow your SharePoint administrator and/or your DBA to configure SharePoint and SQL Server to provide optimal performance for your SharePoint implementation
Integrating Google Cloud Dataproc with Alluxio for faster performance in the ...Alluxio, Inc.
Alluxio Tech Talk
Dec 10, 2019
Chris Crosbie and Roderick Yao from the Google Dataproc team and Dipti Borkar of Alluxio will demo how to set up Google Cloud Dataproc with Alluxio so jobs can seamlessly read from and write to Cloud Storage. They’ll also show how to run Dataproc Spark against a remote HDFS cluster.
For more Alluxio events: https://www.alluxio.io/events/
Modernize Your Existing EDW with IBM Big SQL & Hortonworks Data PlatformHortonworks
Find out how Hortonworks and IBM help you address these challenges to enable success to optimize your existing EDW environment.
https://hortonworks.com/webinar/modernize-existing-edw-ibm-big-sql-hortonworks-data-platform/
Lightning Talk: Why and How to Integrate MongoDB and NoSQL into Hadoop Big Da...MongoDB
Drawn from Think Big's experience on real-world client projects, Think Big Academy Director and Principal Architect Jeffrey Breen will review specific ways to integrate NoSQL databases into Hadoop-based Big Data systems: preserving state in otherwise stateless processes; storing pre-computed metrics and aggregates to enable interactive analytics and reporting; and building a secondary index to provide low latency, random access to data stored stored on the high latency HDFS. A working example of secondary indexing is presented in which MongoDB is used to index web site visitor locations from Omniture clickstream data stored on HDFS.
VMworld 2013: Big Data Platform Building Blocks: Serengeti, Resource Manageme...VMworld
VMworld 2013
Abhishek Kashyap, Pivotal
Kevin Leong, VMware
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
Planning your Next-Gen Change Data Capture (CDC) Architecture in 2019 - Strea...Impetus Technologies
Traditional databases and batch ETL operations have not been able to serve the growing data volumes and the need for fast and continuous data processing.
How can modern enterprises provide their business users real-time access to the most up-to-date and complete data?
In our upcoming webinar, our experts will talk about how real-time CDC improves data availability and fast data processing through incremental updates in the big data lake, without modifying or slowing down source systems. Join this session to learn:
What is CDC and how it impacts business
The various methods for CDC in the enterprise data warehouse
The key factors to consider while building a next-gen CDC architecture:
Batch vs. real-time approaches
Moving from just capturing and storing, to capturing enriching, transforming, and storing
Avoiding stopgap silos to state-through processing
Implementation of CDC through a live demo and use-case
You can view the webinar here - https://www.streamanalytix.com/webinar/planning-your-next-gen-change-data-capture-cdc-architecture-in-2019/
For more information visit - https://www.streamanalytix.com
"Analyzing Twitter Data with Hadoop - Live Demo", presented at Oracle Open World 2014. The repository for the slides is in https://github.com/cloudera/cdh-twitter-example
Lightning Talk: Why and How to Integrate MongoDB and NoSQL into Hadoop Big Da...MongoDB
Drawn from Think Big's experience on real-world client projects, Think Big Academy Director and Principal Architect Jeffrey Breen will review specific ways to integrate NoSQL databases into Hadoop-based Big Data systems: preserving state in otherwise stateless processes; storing pre-computed metrics and aggregates to enable interactive analytics and reporting; and building a secondary index to provide low latency, random access to data stored stored on the high latency HDFS. A working example of secondary indexing is presented in which MongoDB is used to index web site visitor locations from Omniture clickstream data stored on HDFS.
It’s no longer a world of just relational databases. Companies are increasingly adopting specialized datastores such as Hadoop, HBase, MongoDB, Elasticsearch, Solr and S3. Apache Drill, an open source, in-memory, columnar SQL execution engine, enables interactive SQL queries against more datastores.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
3. PresenterInfo
1982 I started working with computers
1988 I started my professional career in computers industry.
1996 I started working with SQL Server 6.0
1998 I earned my first certification at Microsoft as Microsoft
Certified Solution Developer (3rd in Greece)
I started my career as Microsoft Certified Trainer (MCT)
with more than 25.000 hours of training until now!
2010 I became for first time Microsoft MVP on SQL Server
I created the SQL School Greece www.sqlschool.gr
2012 I became MCT Regional Lead by Microsoft Learning
Program.
2013 I was certified as MCSE : Data Platform & Business
Intelligence
Antonios Chatzipavlis
Database Architect,
SQL Server Evangelist
MCT, MCSE, MCITP, MCPD, MCSD, MCDBA, MCSA, MCTS,
MCAD, MCP, OCA, ITIL-F
4. SQLschool.gr
Team
Antonios Chatzipavlis
SQL Server Evangelist • Trainer
Vassilis Ioannidis
SQL Server Expert • Trainer
Fivi Panopoulou
System Engineer • Speaker
Sotiris Karras
System Engineer • Speaker
7. The Conference for Technical Data Professionals
• 200+ technical sessions
• New and expert industry speakers
• Networking opportunities with thousands of attendees
from around the world
Use Local Chapter Discount Code: LC15CPJ8 for $150 off*
October 25-28
Seattle
*Cannot be applied retroactively or combined with other offers.
17. { }
Relational
Cloud
• Disparate systems and processes
• Multiple tools and skillsets
• Siloed insights on
disconnected data
• High cost of ownership
Inefficiencies from fragmented architecture
Beyond relational
On-premises
Challenges of the modern data platform
18. Azure SQL DB
Azure SQL DW
Analytics Platform System
Azure Data Lake
SQL Server 2016
Analytics Platform System
SQL
Relational Beyond relational
On-premisesCloud
Data Management
Power BI
Cortana Analytics
Azure IoT
Business
Analytics
Business Analytics & Data Management Platform
Fits your business
Intelligence made
relevant to your business
Proven leader
19. Access any data Scale and manage Powerful insights Advanced analytics
PolyBase
Insights from data across SQL
Server and Hadoop with the
simplicity of T-SQL
Enhanced SSIS
Designer support for previous
SSIS versions
Enterprise-grade
Analysis Services
Enhanced performance and
scalability for Analysis Services
Single SSDT in Visual
Studio 2015
Build richer analytics solutions as
part of your development projects
in Visual Studio
Enhanced MDS
Excel add-in 15x faster; more
granular security roles; archival
options for transaction logs; and
reuse entities across models
Mobile BI
Business insights for your on-
premises data through rich
visualization on mobile devices
with native apps for Windows,
iOS, and Android
Enhanced Reporting
Services
New modern reports with rich
visualizations
R integration
Bringing predictive analytic
capabilities to your relational
database
Expand your “R” script library with
Microsoft Azure Marketplace
Deeper insights across data
22. Interest in big data spurs customer demand
Increase in number and
variety of data sources
that generate large
quantities of data
Realization that data is
“too valuable” to delete
Dramatic decline in the
cost of hardware,
especially storage
Adoption of big data technologies like Hadoop
$
23. PolyBase and queries
Provides a scalable, T-SQL-compatible query processing
framework for combining data from both universes
24. PolyBase View in SQL Server 2016
PolyBase View
• Execute T-SQL queries against
relational data in SQL Server
and ‘semi-structured’ data in
HDFS and/or Azure
• Leverage existing T-SQL skills
and BI tools to gain insights
from different data stores
• Expand the reach of SQL Server
to Hadoop(HDFS)
26. •PolyBase Engine Service
•PolyBase Data Movement Service (with HDFS Bridge)
•External table constructs
•MR pushdown computation support
Components introduced in SQL Server 2016
27. How to use PolyBase in SQL Server 2016
Set up a Hadoop Cluster
or Azure Storage blob
Install SQL Server
Configure a PolyBase
group
Choose Hadoop flavor
Attach Hadoop Cluster
or Azure Storage
PolyBase T-SQL
queries submitted
here
PolyBase queries can
only refer to tables
here and/or external
tables here
Computenodes
Head nodes
Access any data
28. Step 1: Set up a Hadoop Cluster…
Hortonworks or Cloudera Distributions
Hadoop 2.0 or above
Linux or Windows
On-premises or in Azure
Access any data
29. Step 1: …Or set up an Azure Storage blob
Azure Storage blob (ASB) exposes an HDFS layer
PolyBase reads and writes from ASB using Hadoop
RecordReader/RecordWrite
No compute pushdown support for ASB
Azure
Storage
Volume
Azure
Storage
Volume
Azure
Storage
Volume
Azure
Access any data
30. Step 2: Install SQL Server
PolyBase
DLLs
PolyBase
DLLs
PolyBase
DLLs
PolyBase
DLLs
Install one or more SQL Server instances with PolyBase
PolyBase DLLs (Engine and DMS) are installed and registered
as Windows Services
Prerequisite: User must download and install JRE (Oracle)
Access any data
31. Step 3: Configure a PolyBase group
PolyBase
Engine
PolyBase
DMS
PolyBase
DMS
PolyBase
DMS
PolyBase
DMS
Use stored procedures and GUI to configure nodes as compute
nodes of a PolyBase group
EXEC sp_join_polybase_group
bob.contoso.local, DemoServer, 1433;
EXEC sp_leave_polybase_group;
Head node
Compute nodes
Access any data
32. Step 3: Configure a PolyBase group
PolyBase
Engine
PolyBase
DMS
PolyBase
DMS
PolyBase
DMS
PolyBase
DMS
Head node
Compute nodes
PolyBase scale-out group
Head node is the SQL Server
instance to which queries are
submitted
Compute nodes are used for
scale-out query processing for
data in HDFS or Azure
33. Supported Hadoop distributions
Cloudera CHD 5.x on Linux
Hortonworks 2.x on Linux and Windows Server
What happens under the covers?
Loading the right client jars to connect to Hadoop distribution
-- different numbers map to various Hadoop flavors
-- example: value 4 stands for HDP 2.x on Linux,
value 5 for HDP 2.x on Windows,
value 6 for CHD 5.x on Linux
Access any data
Step 4: Choose Hadoop flavor
34. Step 5: Attach Hadoop Cluster or Azure Storage
PolyBase
Engine
PolyBaseDMS
PolyBaseDMS PolyBaseDMS PolyBaseDMS
Head node
Azure
Storage
Volume
Azure
Storage
Volume
Azure
Storage
Volume
Azure
Access any data
35. After Setup
Compute nodes are used for scale-out
query processing on external tables in
HDFS
Tables on compute nodes cannot be
referenced by queries submitted to
head node
Number of compute nodes can be
dynamically adjusted by DBA
Hadoop clusters can be shared
between multiple SQL16 PolyBase
groups
PolyBase T-SQL
queries submitted
here
PolyBase queries can
only refer to tables
here and/or external
tables here
Computenodes
Head nodes
Access any data
36. PolyBase query example #1
-- select on external table (data in HDFS)
SELECT * FROM Customer
WHERE c_nationkey = 3 and c_acctbal < 0;
A possible execution plan:
CREATE temp
table T
Execute on compute nodes1
IMPORT
FROM HDFS
HDFS Customer file read into T2
EXECUTE
QUERY
Select * from T where
T.c_nationkey =3 and T.c_acctbal < 0
3
Access any data
37. PolyBase query example #2
-- select and aggregate on external table (data in HDFS)
SELECT AVG(c_acctbal) FROM Customer
WHERE c_acctbal < 0 GROUP BY c_nationkey;
Execution plan:
Run MR Job
on Hadoop
Apply filter and compute
aggregate on Customer.
1
What happens here?
Step 1: QO compiles predicate into Java
and generates a MapReduce (MR) job
Step 2: Engine submits MR job to
Hadoop cluster. Output left in hdfsTemp.
hdfsTemp
<US, $-975.21>
<FRA, $-119.13>
<UK, $-63.52>
Access any data
38. PolyBase query example #2
-- select and aggregate on external table (data in HDFS)
SELECT AVG(c_acctbal) FROM Customer
WHERE c_acctbal < 0 GROUP BY c_nationkey;
Execution plan: 1. Predicate and aggregate pushed
into Hadoop cluster as a
MapReduce job
2. Query optimizer makes a cost-
based decision on what
operators to push
Run MR Job on
Hadoop
Apply filter and compute
aggregate on Customer.
Output left in hdfsTemp
1
IMPORT
hdfsTEMP Read hdfsTemp into T3
CREATE temp
table T On DW compute nodes2
RETURN
OPERATION Select * from T4
hdfsTemp
<US, $-975.21>
<FRA, $-119.13>
<UK, $-63.52>
Access any data
41. SSIS improvements for SQL Server 2016
AlwaysOn support
Incremental deployment of
packages
Improved project upgrade support
Error column name support
Custom log level
Package template
OData V4 support
Designer improvements
One designer multi-version support
AlwaysOn
Availability Groups
Secondary for
SSISDB
New York
(Primary)
New Jersey
(Secondary)
SSIS
DB
SSIS
DB
SQL Server 2012
SSIS Project X
SQL Server 2016
SSIS Project X
Improved project
upgrade
Access any data
42. AlwaysOn support for SSISDB
DBA can set up AlwaysOn availability groups
for the SSIS Catalog
Access any data
43. Deploy packages to Integration Services server
private static void Main(string[] args)
{
// Connection string to SSISDB
var connectionString = "Data Source=.;Initial Catalog=SSISDB;Integrated Security=True;MultipleActiveResultSets=false";
using (var sqlConnection = new SqlConnection(connectionString))
{
sqlConnection.Open();
var sqlCommand = new SqlCommand
{
Connection = sqlConnection,
CommandType = CommandType.StoredProcedure,
CommandText = "[catalog].[deploy_packages]"
};
var packageData = Encoding.UTF8.GetBytes(File.ReadAllText(@"C:TestPackage.dtsx"));
// DataTable: name is the package name without extension and package_data is byte array of package.
var packageTable = new DataTable();
packageTable.Columns.Add("name", typeof(string));
packageTable.Columns.Add("package_data", typeof(byte[]));
packageTable.Rows.Add("Package", packageData);
// Set the destination project and folder which is named Folder and Project.
sqlCommand.Parameters.Add(new SqlParameter("@folder_name", SqlDbType.NVarChar, ParameterDirection.Input, "Folder", -1));
sqlCommand.Parameters.Add(new SqlParameter("@project_name", SqlDbType.NVarChar, ParameterDirection.Input, "Project", -1));
sqlCommand.Parameters.Add(new SqlParameter("@packages_table", SqlDbType.Structured, ParameterDirection.Input, packageTable, -1));
var result = sqlCommand.Parameters.Add("RetVal", SqlDbType.Int);
result.Direction = ParameterDirection.ReturnValue;
sqlCommand.ExecuteNonQuery();
}
}
Deployment options
Integration Services Deployment Wizard
SQL Server Management Studio
Deploy packages stored procedure
Object model API
SQL Server Data Tools for Business
Intelligence
Access any data
44. Error column name support
Developer can see the error column name in
both the data viewer and editor
Developer can also see the IntToString
lineage ID mapping in the log
Developer can also programmatically get the
column name using the lineage ID
45. Custom Log level
Developer can create and use a customized
log level other than the default
Access any data
46. Package template
Developer can save part of the package as a
template and reuse it in the design of other
packages
Access any data
48. Capability
Stretch large operational tables
from on-premises to Azure with
the ability to query
Benefits
SQL
Access any data
SSIS improvements for Azure services
50. SQL Server 2016 Reporting Services and mobile reporting
SQL Server 2016
Reporting Services
(Native mode)
Datazen Server now a
component of SSRS
CREATE
SQL Server 2016
Reporting Services
(SharePoint integrated mode)
Datazen Windows app
Datazen Android app
Datazen iOS app
Report Server web portal
(paginated and mobile reports)
Datazen Publisher
SQL Server
Report Builder
Report Designer in
SQL Server Data Tools
Datazen phone app
Pin paginated report elements
to Power BI dashboards
SSRS reports rendered as PDF
SharePoint web
MANAGE CONSUME
51. Render and export reports to PowerPoint® with SQL Server® 2016 Reporting
Services:
•In Report Builder or Report Manager, click Export and choose PowerPoint from
the list
•Pass “PowerPoint” as a parameter in the URL string to render straight to
PowerPoint
PowerPoint Rendering and Export
52. Print reports to PDF from the report viewer toolbar:
•No need to download an ActiveX control
•Page preview shows how the printed pages will look
•Page settings can be configured
•Can also save to PDF format
•Printing is enabled by default, but can disabled
PDF for Remote Printing
53. •Reports now render to HTML5:
•Richer and faster user experience
•Targets modern browsers
•Switch between HTML5 and old rendering engine
HTML5 Rendering Engine
54. •New charts in SQL Server 2016 Reporting Services include:
New Chart Types
Tree Map Chart Sunburst Chart
55. Reporting Services subscriptions have been enhanced with the following
features:
•Native Mode:
• Quickly enable and disable subscriptions. Disabled subscriptions retain configuration properties, so they are
easy to re-enable
• Shared credentials can be used for file share subscriptions. Can be alongside file share with individual
credentials
•SharePoint and Native Mode:
• Include a report description when creating a subscription
• Change the owner of a subscription using the new interface – administrators can also do this using a script
Subscription Enhancements
56. SQL Server 2016 Reporting Services additional enhancements include:
•Reporting Services web portal gives access to users on role-based security
•Use Mobile Report Publisher to publish reports to the web portal for viewing
on mobile devices
•Pin report items to a Power BI dashboard
•Customize the layout of parameters with the new grid-style design surface
•Support for Microsoft .NET Framework
•Report Builder supports High DPI
Other Reporting Services Updates
57. •SQL Server 2016 Mobile Report
Publisher:
• Develop and publish highly visual mobile
reports
• Reports scale to size on tablets and phones
• Data sources include on-premises SQL Server,
Azure SQL Databases, and Excel
• Reports can be viewed in Power BI for iOS—
Power BI must be enabled on the reporting
server
• Compatible with Windows 7 and later
• Stand-alone download from Microsoft
website
• Create and manage KPIs and data sources in
the new Reporting Services
• Find the new Reporting Services web portal
at: http://<server_name>/reports_preview
What are Mobile Reports?
58. •SQL Server Mobile Report Publisher:
• Mobile reports are published to the new SQL Server 2016 Reporting Services
• Both paginated and mobile reports can be rendered and viewed in the new Reporting Services
• Mobile reports can be viewed on an iOS mobile device:
• iPhone and iPad must be iOS 8.0 or later
• iPhone must be iPhone 5 or later
• KPIs can be viewed and created
Publishing Mobile Reports
60. •Create larger data models—data is loaded more efficiently. Improvements to
MDS Add-in for Excel support this increase in capability
•Data compression on the entity level, using row level compression
•Transaction log maintenance and scheduling
•Super User function for easier security management
•Custom indexes
•Manage business rules using the MDS Excel Add-in
•Manage revision history
Enhanced Master Data Services
61. •Perform real-time advanced analytics on operational and analytic data
•R statistical programming language has been integrated into Transact-SQL
•Data scientists can create predictive applications in R and deploy to a SQL
Server 2016 production environment
•R can use SQL Server features including in-memory, columnstore indexes, and
parallel processing
•Execute Transact-SQL procedure with R code from any application that can
connect to SQL Server
•Requires Advanced Analytics Extensions, R Open, R Enterprise, post-install
configurations, and script
Advanced Analytics with R
62. •Set up environments using Configuration Manager
•Connect to any database from your history
•Pin favorite connections for fast access
•Browse SQL Azure databases
•System-versioned temporal tables in database projects
•Multiple languages
•Row level security
•New columnstore index enhancements
•SSIS control flow templates
•SSIS Hadoop connector supports Avro and Kerberos
•Max buffer size in SSIS data flow task increased
•SSAS calculated tables can be created
SSDT in Visual Studio 2015
63. •Tabular Model Scripting Language (TMSL) to automate administrative tasks
•Upgrade to tabular 1200 models, add roles, and upgrade metadata in SSDT
•DirectQuery now available for tabular models
•Partition management for tabular models
•Bi-Directional Cross Filters for tabular models
•Calculated tables in SSDT
•DBCC for Analysis Services
•New assembly to extend AMO
What’s New in SQL Server Analysis Services
64. •More than 50 new DAX functions in SQL Server 2016, including but not limited
to:
• Date and Time Functions—DATEDIFF and CALENDAR
• Filter Functions—ADDMISSINGITEMS
• Information Functions—ISONORAFTER
• Math and Trig Functions—EVEN, PI, SIN, and TAN
• Text Functions—CONCATENATEX
• Other Functions—GROUPBY, INTERSECT, and ISEMPTY
•Named variables are now supported in DAX
•Save incomplete DAX measures
•Improved DAX formatting in the formula bar
Enhanced DAX Functionality
65. •Extended Events for Analysis Services
•Add computer accounts as administrators in SSMS
•Project templates added for tabular 1200 models in SSDT
•New data sources for DirectQuery mode include Teradata, Oracle, and
Microsoft Analytics Platform
•Formula fixup automatically updates measures referencing a table or column
that is renamed (tabular 1200 models only)
Interface Enhancements
66. •Improved performance for generating tabular models in the 1120 compatibility
level up to three times faster
•Tabular model parallel processing functionality for tables with two or more
partitions
•Simpler query generation for DirectQuery delivers better performance
Performance Improvements