Event Location:
Microsoft Offices Midtown Manhattan
1290 Avenue of the Americas
New York City, New York
Abstract:
Big Data entails collecting and analyzing large volumes of data obtained from Web, social media, scientific and other pools of fast-growing event-driven data. Recently, Microsoft announced its Windows Server and Windows Azure implementations of Hadoop, the open source distributed processing engine widely used in Big Data implementations. And the plot thickens, as Microsoft also fits SQL Server business intelligence (BI) tools on top of Hadoop, to make the analysis part of Big Data work with familiar and accessible Microsoft technologies. Come to this session to get an overview of Big Data, Hadoop and its integration with te Microsoft BI stack. See how your skills can be applied to this rapidly growing part of the industry.
Speaker(s): Andrew Brust,
Abstract:
Each application and system is different, but all have a similar quality: there will be times where the systems are used more, and other times where they may appear to be sleeping. Good examples are monthly, quarterly, and yearly for financial systems and the holiday season for retail. The last thing you want to have in these time frames is your CxO standing at your desk wondering why things are slow or possibly down. Ensuring that your SQL Servers are optimally configured for those heavy usage periods cannot be done with a wing and a prayer – you need an actionable, realistic plan. This session will discuss how to guarantee that your SQL Server instances and the configurations they use are as scalable and reliable as possible.
Speaker(s): Ben DeBow,
Abstract:
A large volume of analysis that a business typically performs on its data involves dates and/or times. For example, you may need to compare sales from one year to the next or aggregate transactions over time. DAX incorporates many built in time intelligence functions to help make date-time based calculations easier. Although the time intelligence functions are very beneficial, they can be misused and give erroneous results. To avoid this, it is imperative that you understand what functions to use and how to use them. This session is designed to guide you through the various time intelligence functions available in DAX and provide practical examples of how to use them.
Speaker(s): Dan Clark,
Abstract:
Fuzzy Matching, Similarity Matching or Record Linkage is the most critical and least understood process in any Data Warehouse, BI, Integration, Big Data , Data Quality, MDM , Social Network or integrating crap effort. Over at LinkedIn there is Group run by Henrik Liliendahl Sorensen for Data Matching, Bill Winkler, principal researcher at the US Census" has written a series of white papers on record linkage and particular a technique called "Blocking Indexs". In addition we wil cover William Cohen Research Professor, Machine Learning Department, Carnegie Mellon University white papers an implementations. Presented will be our collection of "real world" examples(Code) and you will leave a master of record linkage and the concepts behind it
Speaker(s): Ira Warren,
Abstract:
It might seem far-fetched that a company would upgrade to SQL Server 2012 “just” for a database index. But after you see the performance enhancements gained from the new columnstore index in SQL Server 2012, you’ll see why many are calling this one of the most important features in the history of SQL Server. In this presentation, I’ll talk about the physical aspects of columnstore index in SQL Server 2012, how to create it, and what environments (mainly data warehousing environments) and queries can make use of it. I’ll show performance benchmarks between columnstore indexes in SQL Server 2012, and compare them to index strategies prior to SQL Server 2012. I'll also show how the new Batch execution mode can improve performance as well
Speaker(s): Kevin Goff,
Abstract:
Let’s face it. You can effectively do many IT jobs related to SQL Server without knowing the internals of how SQL Server works. Many great developers, DBAs, and designers get their day-to-day work completed on time and with reasonable quality while never really knowing what’s happening behind the scenes. But if you want to take your skills to the next level, it’s critical to know SQL Server’s internal processes and architecture. This session will answer questions like: - What’s different about 32- and 64-bit systems? - What are the various areas of memory inside of SQL Server? - How are queries handled behind the scenes? - What does SQL Server do with procedural code, like functions, procedures, and triggers? - ...and much more.
Speaker(s): Kevin Kline,
Abstract:
Today's large data fields (LDF) are full of unstructured information stored in varchar, text, varbinary or xml data types. How do you write an application to search the column for patterns? Traditional SQL techniques using a column INDEX and LIKE operator result in a query plan that contains a full table scan. I will be introducing the brother's grimm database that has the full text of each fairy tale. I will create a full text catalog / index, select a change tracking strategy, define optional stop list / thesaurus file, and then populate the index. I will use CONTAINS and FREETEXT operators in SELECT queries to leverage the FTI. This resulting query plan performs index seek.
Speaker(s): John Miner,
Abstract:
As SQL Server evolves, so does Microsoft continue to improve and enhance Transact SQL (T-SQL). In SQL Server 2012, T-SQL remains the primary language for programming the relational database engine. In this informative and demo-packed session, Lenni will guide you through the T-SQL enhancements in the very latest release of SQL Server. We’ll dive into powerful new windowing enhancements with the OVER clause, running and sliding aggregations, new T-SQL functions (all 22 of them!), improved error handling with THROW, server-side paging with OFFSET/FETCH NEXT, sequence generators, and rich metadata discovery techniques. If you want to learn the new T-SQL enhancements in SQL Server 2012, you won’t want to miss out on this session!
Speaker(s): Leonard Lobel,
Abstract:
With the release of SQL Server 2012, the new SQL Server Data Tools serves as your primary development environment for building applications on top of SQL Server. SSDT plugs in to Visual Studio with tooling designed specifically for the application developer. With SSDT, developers no long need to constantly switch between VS and SSMS. In this session, Lenni demonstrates how SSDT is used to develop for (and deploy to) on-premise and SQL Azure databases. You will learn how to use code navigation, IntelliSense, and refactoring with your database model, and how to design databases offline and under source control right from VS. Don’t miss out on this demo-centric information-packed session on the next generation of database tools for developers!
Speaker(s): Leonard Lobel,
Abstract:
Data mining as a technology is designed to analyze large volumes of data looking for patterns that accurately predict behavior. These patterns can then be used to derive knowledge about data, and in turn this knowledge can be used to enhance application designs and the user experience. In this presentation, you will be introduced to Microsoft SQL Server 2005 and 2008 Data Mining and demonstrations on how to develop data mining models that can be embedded into your applications. Demonstrations are based on SQL Server 2008 R2 Data Mining. This presentation is a must for any developer looking to embed “Artificial Intelligence” into their solution design to take their applications to the next level.
Speaker(s): Peter Myers,
Abstract:
Gone are all the spaghetti errors of past versions of SQL. For example did you know that BEGIN TRAN…COMMIT TRAN is not enough to make everything work together? People are often shocked when they see the demo in this talk where the first statement fails and all others statements still commit. This can still happen to you in SQL 2012 if you are not aware of the options. In fact did you know that when SQL encounters an error of Severity 11 (or higher), there a 4 different ways it can react? Learn how to predict the Error Action and control it. This is possible with or without structured error handling. See both ways to control the outcome to the way you want it.
Speaker(s): Rick Morelan,
Abstract:
With more and more companies moving to a cloud solution, the necessity to easily and efficiently scale their database solution is critical. This session will discuss how to scale SQL Azure using SQL Azure Federations, a recent addition to SQL Azure that provides the ability to build scalable, elastic, and multi-tenant solutions in SQL Azure. SQL Azzure Federations bring the sharding pattern into SQL Azure as a first class citizen as a way to achieve greater scalability and performance from the database tier of your application through horizontal partitioning at the database level. This session will look at Federations from a real-world point of view, by applying Federations to a real-life database. We will also look at performance benefits.
Speaker(s): Scott Klein,
Abstract:
Stored procedures and functions are the mainstay of SQL Server coding. In this presentation you will learn techniques to locate problem code and to improve it's performance. Step 1 is to discover where the time is going using server traces, code to analyzes the traces, and the new Extended Events. Once we know where the time is going we look at strategies to improve performance: Managing indexes on temp tables and why heaps are often the best choice for temp tables; determining if an index is helping; Rewriting scalar and multi-statement functions as inline functions and why it’s so important; mastering minimally logged operations and the “Go Faster” switch. Each technique is illustrated with examples
Speaker(s): Andrew Novick,
Abstract:
If you have wanted to learn how to use Extended Events and have had a hard time trying to figure out where to start then this session is for you. This session is designed for someone that has never used Extended Events before. After this session you will know the basics of how to setup and use this highly scalable and configurable architecture to trouble shoot server issues. You will see how to use them in SQL 2008 and how they have been beefed up in SQL 2012. This will be a demo rich session so come prepared to finally get to know Extended Events.
Speaker(s): AJ Mendo,
Abstract:
You say you have a backup strategy, but what is your recovery strategy? In this session I will demonstrate several methods for performing much-needed backups and how to recover those backups to include FULL, DIFFERENTIAL, FILE GROUP, and TRANSACTION LOG. He will also demo performing a peace meal restore as well as backing up and restoring the tail end of the log after the data file becomes corrupt. I will discuss industry best practices for backing up and recovering your data. The goal of this session is to educate you on the various backup strategies so you can decide which is best for your organization, demonstrate how to recover your databases, and to create the desire for you to go back and validate your current strategies
Speaker(s): Tim Radney,
Abstract:
You rarely hear of a data integration project that doesn't involve a spreadsheet as a source document, a lookup reference, or an output. It's the ambiguously ubiquitous container for business data because it's so flexible and familiar to users. Unfortunately, the same features those business users crave tend to cause huge problems for data professionals. In this session we'll look at typical integration issues with Excel, explain why they occur, and show you more options than just the Excel Source or COM API. In a world where spreadsheets are the "database of choice" for business users, knowing how to get SSIS to interact reliably with Excel is an essential skill.
Speaker(s): Todd McDermid,
Abstract:
The Analysis Services 2012 Business Intelligence Semantic Model (BISM) unifies Multidimensional (OLAP) and Tabular (relational) options for organizational BI. BI professionals can implement Multidimensional cubes, or they can deploy Tabular models developed by business users to a dedicated server. Those new to Tabular, or those embarking upon BI for the first time with Analysis Services 2012, may find it difficult to choose between the two paths. In this session, BI Architect and MVP Bill Pearson overviews the nature and design goals of each option, comparing Multidimensional and Tabular features. He then offers guidance on selecting the appropriate model, providing real world examples to illustrate approaches for given scenarios.
Speaker(s): William E Pearson III,
Abstract:
SQL Server 2012 PowerPivot will allow analysts to use Excel 2010 to load and prepare large volumes of data from various data sources to create a data model. The data model can then be enriched with calculations to become a data source for Excel PivotTable, PivotChart and CUBE function reports. And as compelling as these BI experiences can be that’s not the end of the story. A PowerPivot workbook deployed to SharePoint Server 2010 can be used to create even more compelling BI experiences using Reporting Services and PerformancePoint Services. In this presentation learn about the fundamentals of PowerPivot data model creation, and the exciting ways PowerPivot data models can be used to visualize and share data.
Speaker(s): Peter Myers,
Abstract:
PowerShell is a command-line scripting language primarily designed for system administration development. Unlike VBScript or DOS batch files, PowerShell is built upon the .NET Platform which makes it customizable and extensible. This introductory session will show the PowerShell language constructs scripts and how it can be used for SQL Server administration (using SMO WMI providers) and development (ADO.Net OLEDB providers).
Speaker(s): SB Chatterjee,
Abstract:
See those things around your ankles?  Whether you're an accidental DBA, a DBA who has just inherited a bunch of servers, or someone who works in a shop that won't buy monitoring tools, this session will help you get basic monitoring in place to make sure you know what's going on in your environment. You'll learn how to implement seven simple scripts that perk their ears up and start barking like a dog after a stranger walks in the house. They are the canary in your coal mine. You'll know when backups fail, when they run longer than usual, when data files are getting full, when transaction logs have excessive VLFs, and more.
Speaker(s): Mike Hillwig,
Abstract:
Solid State Drives (SSD) are becoming one of the mainstream storage solutions, and many firms have started placing SQL Server database files on SSD in hope of gaining performance. However, how to best run SQL Server on SSD is not a settled question. Conflicting opinions abound. This session is packed with first-hand data points, sharing with you the results from a series of extensive performance tests on SSD, either with or without SQL Server. You will learn the basic performance characteristics of SSD, and what SQL Server/SSD configurations may give you best results.
Speaker(s): Linchi Shea,
Abstract:
In my session, I will offer some practical tips and tricks on a wide-array of Index Analysis methods that will allow you to find out everything about a client's indexes and were afraid to ask! What better way to optimize the performance of the database than talk about their indexes. What do you need to know in order to make these suggestions, and implement them. This session will cover the basics on indexes, and then demonstrate ways to improve DB performance. Missing Indexes, Duplicate Indexes, Fragmented Indexes, Covering Indexes, Clustered Nonclustered indexes, and the queries that love them. I will also demo ways in which you can correlate the worst performing queries with missing indexes
Speaker(s): Robert Pearl,
Abstract:
This session will take an exploratory look at Microsoft's cloud-based relational database offering. We'll lift the hood and look at its many benefits and features, and how it easily fills the need for a highly available and scalable database service in the cloud. We'll discuss how SQL Azure helps ease provisioning and deployment, and how Microsoft takes care of the physical administration so that developers and DBA's alike can focus on the aspects of their job they really care about.
Speaker(s): Scott Klein,
Abstract:
Creating a query plan can be a time consuming and expensive process. To avoid repeating these costly steps, SQL Server stores its query plans, in the plan cache where they can be reused as needed. In this session, we’ll look at how the plan cache is organized, what plans are saved, when plans are reused and when they are recreated, methods for observing the contents of the plan cache, and finally, methods for manipulating plan reuse and recreation.
Speaker(s): Christina Leo,
Abstract:
Mike Hillwig is known as the Cranky DBA. You probably have pain points in your environment that make you cranky, too. Mike has lots of horror stories to tell about bad SQL Server implementations and practices. More importantly, he has developed a list of 12 key tips for managing your SQL Server environment. By following these tips, you’ll make your DBAs, developers, and system administrators a little less cranky.
Speaker(s): Mike Hillwig,
Abstract:
In this demo-rich presentation, Brian shows you some of the common and not so common ways to tune SQL Server Integration Services (SSIS). Learn how to tune the data flow using some of the advanced SSIS options and how to avoid common SSIS mistakes. See how to measure performance and how to keep SSIS from monopolizing your server's resourcing. Lastly, discover SQL Server 2008 and 2012 features that will make SSIS more efficient.
Speaker(s): Brian Knight,
Abstract:
Bad Windows builds? No HA? No backups? SQL Server considered the non-mission critical platform yet you have hundreds of instances? Over the years I've seen most, if not all of, the good, bad, and ugly of being a SQL Server DBA from being both a full time employee as well as a consultant. If you want to skip 20 years of ups and downs, come to this session to hear how you can be a better DBA for your SQL Server deployments, avoid pitfalls, and hopefully laugh at a few of my misadventures over the course of my career.
Speaker(s): Allan Hirt,
Abstract:
In this session, you'll learn how to cleanse your data and apply simple to complex business rules in SSIS. Learn how to solve complex data problems quickly in SSIS using Data Quality Services (DQS). The speaker will show you how to incorporate scripting into your SSIS data flow to find and fix bad data. Then he'll show how to use advanced fuzzy logic to satisfy data duplication issues. Lastly, he’ll show you how to implement advanced data cleansing and normalization in SQL Server 2012 SSIS with DQS and MDS.
Speaker(s): Brian Knight,
Abstract:
Replication is a native SQL Server component which is used for copying, distribution and aggregating data between databases and servers. In this presentation SQL Server MVP discusses the different replication types and technologies and their sweet points. He also shows common use cases, gotcha's, and performance tuning and troubleshooting techniques.
Speaker(s): Hilary Cotter,
Abstract:
An SQL Server database is resource-intensive by its very nature and one of the most resource-intensive Business Critical applications you will ever virtualize. If best practices are not followed, the database will never perform as needed. This presentation will teach the DBA best practices for Virtualizing SQL Server on VMware. Key Takeaway 1 Key Database Best Practices Key Takeaway 2 Common Mistakes How to Avoid Them Key Takeaway 3 Many resources available and where to find them
Speaker(s): Michael Corey,
Abstract:
Do you really understand SQL Servers’ Concurrency behaviour?  Do you believe Read operations cannot start a Transaction? Do you really know if READ_UNCOMMITTED is safe for reporting? Is being Optimistic really better than being Pessimistic? Can SQL Server 2012 be the solution to all our problems or our worst nightmare? I look forward to you joining me in this very revealing and thought provoking session where I will provide answers to all these questions and more and make you wish you had known all of this sooner.
Speaker(s): Mark Broadbent,
Abstract:
SSRS 2012: Having just completed a PRACTICAL dashboard to answer JUST this exact question, we shall be looking at how to create a reporting tool that will provide YOUR management with all their answers. We shall be focusing on the plethora of information that may be reaped from Dynamic Managment Views (DMV) and see how KPI's may be incorporated into the mix.
Speaker(s): Steve Simon,
Abstract:
Snapshot fact tables are a common approach when a point-in-time reference is required. In some cases though, even snapshots are not an option due to the amount of data it will generate. In this session we will walk through a practical example of when and how to implement temporal fact tables, and how these can be a viable alternative to snapshots in certain situations.
Speaker(s): Martin Schoombee,
Abstract:
Considering a promotion into management? This session will teach you the fundamental skills needed to effectively lead an IT team. Topics include motivational skills, conflict resolution skills, communication skills and project/job tracking skills. Attendees will also learn: 1. How to motivate a team and keep the members of that team focused and on task. 2. How to resolve conflicts, address performance problems, and handle project/job missteps. 3. How to gain support for your ideas, earn upper management support, and communicate with top management.
Speaker(s): Kevin Kline,
Abstract:
Get an overview of the problem domain, architecture and solution space for Data Quality Services. See how Data Quality Services works hand-in-hand with Master Data Management to create master data, matching rules and leverage both to deduplicate data
Speaker(s): Marc Jellinek,
Abstract:
If you've ever found yourself stating the above, this session is for you. For many developers, writing T-SQL that works is not the challenge. But too often, functional T-SQL is not the same as good T-SQL. In this session, we will examine why "SQL that works" is not good enough. Understanding indexes, exectuion plans, sargability, and more are all critical to writing good T-SQL. We will also examine several real-world examples of T-SQL that "worked great in dev" but caused major issues when it hit production.
Speaker(s): Randy Knight,
Abstract:
This is a demo-driven session that will focus on designing and implementing a multi-site, geographically dispersed SQL Server 2012 Failover Cluster instance across multiple data centers. We will cover the considerations on implementing such an architecture to address high availability and disaster recovery requirements for your mission-critical databases.
Speaker(s): Edwin Sarmiento,
Abstract:
Practical XML usage for SQL Server 2005 and up. Working examples how to load, create, and shred the XML using XPath query methods. The XML tips and tricks.
Speaker(s): Alex Grinberg,
Abstract:
You want to deploy AlwaysOn, but you're concerned about hidden drawbacks, performance impacts, and how it affects development. Brent Ozar has deployed SQL 2012 Availability Groups at big web sites including StackOverflow.com and the Discovery Channel, plus used it to scale out reads at data warehouses. Come learn what he's found in real-life deployments of AlwaysOn.
Speaker(s): Brent Ozar,
Abstract:
Creating a performance baseline for a SQL Server instance provides many benefits including defining a starting point for optimization efforts, documenting the server, a reference point for capacity planning, and providing a reference for ongoing performance comparison. This session will provide a detailed presentation of an approach for collecting, storing, and presenting performance metrics for use in developing a baseline performance assessment of a SQL Server instance.
Speaker(s): Ron Johnson,
Abstract:
It’s one thing to have a high-level understanding of Big Data, Hadoop and MapReduce; it’s quite another to feel comfortable working with the tools. In this demo-heavy session, ZDNet Big Data blogger and Visual Studio magazine columnist Andrew Brust will take a look at actual MapReduce code and see Hadoop ecosystem components HBase, Hive, Pig and Mahout in action.
Speaker(s): Andrew Brust,
Abstract:
In this diverse session we will take an in-depth look at moving to the SQL 2012 platform and the upgrade strategies at your disposal. Specifically we will take a deep dive into preparing and reporting for upgrade, upgrade strategies, performing the upgrade and knowing the upgrade was successful. This session will also look at several advanced scenarios such as migrating to SQL Server 2012 on Server Core, AlwaysOn Availability Groups and AlwaysOn Fail-over Clustered Instances. Attend this must see session and you too can have the “Moves like Jagger”.
Speaker(s): Mark Broadbent,
Abstract:
There are many treatments of table design for slowly changing dimenions, and almost as many on doing ETL on an SCD. Much less has been said about building a cube around a slowly changing dimension. In this session, Mark will review the types of slowly changing dimensions, describe the performance implications of various methods of loading SCDs in SSIS (SCD task, Lookups, Merge, and Script component), and build the versioning directly into the dimension in Analysis Services
Speaker(s): Mark Stacey,
Abstract:
SQL Server speed boils down to how fast we can get data in and out of storage. Sooner or later, we're going to run out of memory to cache. In this session, we take a lesson from Microsoft's blazing-fast Fast Track Reference Architectures, look at why they work so well for the wildest queries, and explain how to build our own SQL Servers for quick queries. Brent Ozar shows you how to test your own servers and compares them to servers he's worked with in the field.
Speaker(s): Brent Ozar,
Abstract:
SSRS 2008 R2 has been a game changer for SQL Server in terms of visualization techniques. With a wide range of available options for charting, BI professionals struggle to get familiar with even the basic functionalities of most charts. This session will talk about the basic functionalities of all the charts as well as some tips and tricks around them. Come to this session and take your charting skills to the next level.
Speaker(s): Jason Thomas,
Abstract:
SQL Server DBAs have relied so much on graphical user interface (GUI) to administer and manage database servers. So, why take away the GUI? If you’re more into using the command-line and PowerShell to manage your servers, come to this session to learn how to implement SQL Server 2012 on Windows Server Core
Speaker(s): Edwin Sarmiento,
Abstract:
In this presentation, I'll go through all the new features in SQL Server 2012. I won't cover any one area heavily - the goal is just to identify (and in some cases, briefly show) as many new features as possible....from the new columnstore index, to T-SQL enhancements, to a greatly iimproved SSIS tool, to a new model for creating analytic databases, and more. SQL Server 2012 has a large amount of new functionality that helps all sorts of database developers. After this presentation, I can almost promise you'll be VERY interested in upgrading to SQL Server 2012.
Speaker(s): Kevin Goff,
This is a list of speakers from the XML Guidebook records. The details and URLs were valid at the time of the event.
Hilary Cotteris a 20 year IT veteran who has answered over 20,000 questions on the forums. Some of them correctly. He specializes in HA technologies, especially replication, performance tuning, full-text search, and SQL Server Service Broker. Hilary is also an author, or contributor on a number of books on SQL Server.
Contact: http://www.bidn.com/people/brianknight
Brian Knight, a SQL Server MVP, MCSE, and MCDBA, is the owner and founder of Pragmatic Works. He is also the co-founder of SQLServerCentral.com, BIDN.com, and SQLShare.com. Brian runs the local SQL Server users group in Jacksonville (JSSUG), is a contributing columnist at several technical magazines, and does regular webcasts at PragmaticWorks.com. He is the author of 15 SQL Server books and a frequent speaker at conferences such as PASS Summit, SQL Connections, TechEd, and many Code Camps.
LinkedIn: https://uk.linkedin.com/in/retracement
Contact: http://tenbulls.co.uk
Mark Broadbent is a Microsoft Certified Master in SQL Server, Chapter Leader, Virtual Chapter Leader, SQLSaturday Cambridge and SharePoint Saturday Cambridge founder (the UKs first SQLSaturday) and awarded Microsoft#39;s Community Contributor award in 2011 and the PASS Outstanding Volunteer award in 2012. Mark is a regular speaker at both International and National events and is an expert in HADR solutions, SQL Server migration, and SQL Server Concurrency control.
LinkedIn: http://linkedin.com/in/tradney
Contact: http://www.timradney.com
Tim is a Data Platform MVP and has a whole collection of Microsoft and other industry certifications. His experience includes HA/DR, virtualization, SSIS, SSRS, and performance tuning, among everything else SQL Server-related. Tim is very active and passionate in the SQL Community. He runs the Columbus GA SQL Users Group, has been a PASS Regional Mentor for a number of years, was named a PASS Outstanding Volunteer in 2012, and is a frequent speaker at user groups, SQLSaturdays and PASS Summits. Tim is one of the top ranked in karma on ask.sqlservercentral.com, answers questions as @tradney on Twitter, and blogs at http://timradney.com and SQLskills blog at http://www.SQLskills.com/blogs/tim.
Contact: http://christinaleo.net
Christina Leo is a Cloud Solution Architect at Microsoft specialising in the Data and AI Platform. Prior to joining Microsoft in 2016, she worked as an independent consultant focusing on T-SQL and BI development, as well as database performance tuning in the finance and investment banking sector. When she isn't sharing her 18 years of technical experience with the data community, you can find her racing around the Solent on a 40' sailboat or often in the Thames on a little Laser.
Contact: http://www.bidn.com/people/brianknight
Brian Knight, a SQL Server MVP, MCSE, and MCDBA, is the owner and founder of Pragmatic Works. He is also the co-founder of SQLServerCentral.com, BIDN.com, and SQLShare.com. Brian runs the local SQL Server users group in Jacksonville (JSSUG), is a contributing columnist at several technical magazines, and does regular webcasts at PragmaticWorks.com. He is the author of 15 SQL Server books and a frequent speaker at conferences such as PASS Summit, SQL Connections, TechEd, and many Code Camps.
Contact: http://www.neudesic.com
Marc Jellinek is a Principal Consultant with Neudesic, focused on the Business Intelligence space. He has worked with every version of SQL Server since 6.0; with experience in leveraging the strengths of the relational database, Analysis Services, Integration Services and Reporting Services. He gained his experience working for Ernst Young, MLB Network and Microsoft.
Contact: http://www.KevinSGoff.net
Kevin S. Goff (http://www.kevinsgoff.net) is a Microsoft SQL Server MVP Database architect/developer/speaker/author Regular columnist for CoDe Magazine on .NET, SQL Server, and Business Intelligence topics Frequent speaker at community events in the Mid-Atlantic region. Host of BDBI Radio (http://www.bdbiradio.com), a weekly webcast on SQL/BI topics
LinkedIn: http://www.linkedin.com/in/mikehillwig
Contact: http://www.mikehillwig.com
Veteran DBA Mike Hillwig is a native Pittsburgher and resident of the Boston Suburbs. He’s a DBA Manager for a financial software company that’s owned by one of the world’s largest bank. Mike has been working with SQL Server since version 7 and has a background in infrastructure and network. Today, he manages a team of DBAs around the globe.
Contact: http://sqlblog.com/blogs/linchi_shea/
LinkedIn: https://uk.linkedin.com/in/retracement
Contact: http://tenbulls.co.uk
Mark Broadbent is a Microsoft Certified Master in SQL Server, Chapter Leader, Virtual Chapter Leader, SQLSaturday Cambridge and SharePoint Saturday Cambridge founder (the UKs first SQLSaturday) and awarded Microsoft#39;s Community Contributor award in 2011 and the PASS Outstanding Volunteer award in 2012. Mark is a regular speaker at both International and National events and is an expert in HADR solutions, SQL Server migration, and SQL Server Concurrency control.
LinkedIn: http://www.linkedin.com/pub/john-miner/a/85a/889
Contact: http://www.craftydba.com
John has over twenty years of IT experience including a Masters degree in Computer Science from the University of Rhode Island with concentrations in database technologies and programming languages. He also has Microsoft Certificates for Database Administration (MCDBA) and System Admistration (MCSA). John is currently a Senior SQL Server Developer / Administrator in charge of best practices by the IT team at Sensata Technologies.
LinkedIn: http://www.linkedin.com
Contact: http://www.sqlservercentral.com/blogs/pearlknows/
Robert Pearl is a 5-year SQL Server MVP and creator of the award-winning database and monitoring alert system, SQLCentric. Author of the HealthySQL - Comprehensive Guide to Healthy SQL Server Performance. He’s the founder of Pearl Knowledge Solutions. As a SQL Server community evangelist, he covers local SQL Server events in the New York City area and maintains the Pearl Knows blog. Voted TOP BLOGGER in 2011.
LinkedIn: http://www.linkedin.com/in/randyknight
Contact: http://www.sqlsolutionsgroup.com/blog
Randy Knight is a data professional who has worked with Microsoft technology for over 25 years, focusing on SQL Server since 1997. He has worked in a variety of settings, including 6 years as a database architect for match.com. In 2010, he founded SQL Server Solutions Group LLC, a boutique SQL Server consultancy. A Microsoft Certified Master (MCM) in SQL Server, he speaks often at events all over the country including the PASS Summit, SQLIntersections, and numerous SQLSaturday and User Groups.
Rick has worked more than 12 years at Microsoft and has attained over 30 Microsoft technical including certifications in applications, networking, databases and .NET development (MCDBA, MCTS, MCITP, MCAD, MOE, MCSE, MCSE+I). He has also provided training for NW University, Volt Technical Education, The DigiGirlz, and Microsoft. Rick is the Author of the 5 volume SQL Joes 2 Pros book series.
LinkedIn: http://www.linkedin.com/in/mikehillwig
Contact: http://www.mikehillwig.com
Veteran DBA Mike Hillwig is a native Pittsburgher and resident of the Boston Suburbs. He’s a DBA Manager for a financial software company that’s owned by one of the world’s largest bank. Mike has been working with SQL Server since version 7 and has a background in infrastructure and network. Today, he manages a team of DBAs around the globe.
LinkedIn: http://www.linkedin.com/in/martinschoombee
Contact: http://www.martinschoombee.com
Martin is an independent Business Intelligence Analytics consultant, helping customers make sense of their data for more than 15 years.
Contact: http://MarkGStacey.net
Mark Stacey founded the Aphelion Software Group, and works tirelessly to cross the business/technical boundaries in Business Intelligence, working in both SharePoint and SQL. He has published two books on BI - Sharepoint 2010 BI and Visual Intelligence and frequently speaks at both SQLSaturday and SharePoint Saturday events. Mark is one of the few Microsoft PDW trainers, and has trained in Africa, India and Europe on the PDW, as well as all over the world on other technologies
Contact: http://www.zdnet.com/blog/big-data
Andrew J. Brust is the Senior Director, Market Strategy and Intelligence at Datameer and writes a blog for ZDNet called quot;Big on Dataquot; (bit.ly/bigondata). Andrew is co-author of quot;Programming Microsoft SQL Server 2012quot; (Microsoft Press); an advisor to the NY Technology Council; serves as Microsoft Regional Director and MVP; is conference co-chair of Visual Studio Live!; and writes Visual Studio Magazine#39;s quot;Redmond Reviewquot; column.
Contact: http://KevinEKline.com
Kevin Kline is the Director of Engineering Services at SQL Sentry. A Microsoft SQL Server MVP, Kevin is a founding board member of PASS, editor-in-chief of SQLServerPedia.com and the author of popular IT books like “SQL in a Nutshell” (O’Reilly Associates). His twitter handle is @kekline and he blogs at http://KevinEKline.com. Kevin is a top-rated speaker at industry trade shows and has been active in the IT industry for over 20 years.
Peter has 14 years of solid experience working in OLTP database design and Business Intelligence with SQL Server and SharePoint. In April 2012, Peter was awarded Microsoft MVP (Most Valuable Professional) for a sixth time. Peter enjoys sharing his enthusiasm for Microsoft technologies by presenting at SQL Server user group meetings and technical events, including TechEd in North America, Europe and Australia.
LinkedIn: https://www.linkedin.com/in/alex-grinberg-36773a6/
I have more than 20 years of IT experience. My primary focus is with the latest Microsoft technologies including .NET (VB and C#), SSRS and SSIS. I provide services in tuning, optimization, analysis and development for the creation of new applications, converting legacy technologies (SQL Server, VB.NET and C# ) and site training. I have worked for CSC, VerticalNet, IDP, LSAC , and TMNAS (to name a few) and I am currently employed with Cox Automotive. I am Apress author book "XML and JSON Recipes for SQL Server", also wrote number of articles for Simple-Talk and SQLServerCentral.com
LinkedIn: http://www.linkedin.com/in/lennilobel
Contact: http://lennilobel.wordpress.com
Leonard Lobel (Microsoft MVP, Data Platform) is CTO and co-founder of Sleek Technologies, Inc., a New York-based development shop with an early adopter philosophy toward new technologies. He is also a principal consultant at Tallan, Inc., a Microsoft National Systems Integrator and Gold Competency Partner. Programming since 1979, Lenni specializes in Microsoft-based solutions, with experience that spans a variety of business domains, including publishing, financial, wholesale/retail, health care, and e-commerce. Lenni has served as chief architect and lead developer for various organizations, ranging from small shops to high-profile clients. He is also a consultant, trainer, and frequent speaker at local usergroup meetings, VSLive, SQL PASS, and other industry conferences. Lenni has also authored several MS Press books and Pluralsight courses on SQL Server programming.
LinkedIn: https://www.linkedin.com/in/brentozar
Contact: https://www.BrentOzar.com
Brent Ozar loves to make SQL Server faster. He created sp_Blitz and the SQL Server First Responder Kit. He shares what he's learned at BrentOzar.com.
LinkedIn: https://www.linkedin.com/in/michael-corey/
Contact: http://michaelcorey.com/
Michael is a Director Cloud Computing Evangelist for Spectrum Enterprise Navisite. In 2017, was recognized as #42 of the top 100 most influential people in the “cloud industry”. Michael's a recognized Microsoft Data Platform MVP formerly (Microsoft SQL Server MVP), recognized Oracle ACE, a recognized VMware vExpert and has worked with relational databases for over 30 years starting with Oracle Version 3. Michael is a Past President of the Independent Oracle Users Group (IOUG), A Founder of the Professional Association of SQL Server and current President of the IOUG VMware Special Interest Group. Michael is the original Oracle Press author, frequent blogger http://michaelcorey.com/, a regular columnist for the Big Data Quarterly
Over 35 years experiences in Software Sevelopemt, IT Management and BI Architecture.
Contact: http://aka.ms/sqlscott
Scott Klein is a senior consultant with SQL Solutions Group with over two decades of experience working with Microsoft SQL Server. Prior to SSG, Scott spent almost 10 years at Microsoft, traveling the globe as a technical evangelist training and speaking about SQL Server and Microsoft’s Azure data services. Scott’s recent focus has been on advanced analytics, including big data and IoT, providing real-world training to help bring intelligence to your data. Scott has authored several books focusing on data and data analytics. Scott is continuously striving and looking for ways to help developers and companies grok the wonderful world of data.
LinkedIn: https://www.linkedin.com/pub/allan-hirt/1/b72/673
Contact: http://www.sqlha.com/blog
SQLHA, LLC founder, consultant, trainer, author, and business continuity, infrastructure, and virtualization expert Allan Hirt has been working with SQL Server since 1992 when it was still a Sybase product. He has also been clustering in Windows Server since the late 1990s when it was known as Wolfpack. Currently a dual Microsoft MVP (Data Platform; Cloud and Datacenter Management) as well as a VMware vExpert, Allan works with all sizes of customers, no matter if they are on premises or in the public cloud. He also delivers training and speaks at events over the world.
Peter has 14 years of solid experience working in OLTP database design and Business Intelligence with SQL Server and SharePoint. In April 2012, Peter was awarded Microsoft MVP (Most Valuable Professional) for a sixth time. Peter enjoys sharing his enthusiasm for Microsoft technologies by presenting at SQL Server user group meetings and technical events, including TechEd in North America, Europe and Australia.
LinkedIn: http://www.linkedin.com/in/dxclark/
Contact: http://drclarkblog.wordpress.com/
Dan Clark is a senior data analytics consultant. He is focused on all things data analytics and training others how to get value from their data. Dan has published several books and numerous articles on .NET programming and data analytics. He is a regular speaker at various developer and database conferences and user group meetings and enjoys interacting with the Microsoft developer and database communities. His latest book Beginning Power BI published by Apress is a will get you up and running with self-service data analytics on the Power BI platform in no time.
Contact: http://www.zdnet.com/blog/big-data
Andrew J. Brust is the Senior Director, Market Strategy and Intelligence at Datameer and writes a blog for ZDNet called quot;Big on Dataquot; (bit.ly/bigondata). Andrew is co-author of quot;Programming Microsoft SQL Server 2012quot; (Microsoft Press); an advisor to the NY Technology Council; serves as Microsoft Regional Director and MVP; is conference co-chair of Visual Studio Live!; and writes Visual Studio Magazine#39;s quot;Redmond Reviewquot; column.
Contact: http://KevinEKline.com
Kevin Kline is the Director of Engineering Services at SQL Sentry. A Microsoft SQL Server MVP, Kevin is a founding board member of PASS, editor-in-chief of SQLServerPedia.com and the author of popular IT books like “SQL in a Nutshell” (O’Reilly Associates). His twitter handle is @kekline and he blogs at http://KevinEKline.com. Kevin is a top-rated speaker at industry trade shows and has been active in the IT industry for over 20 years.
Contact: http://bassplayerdoc.wordpress.com
Edwin Sarmiento is a SQL Server MVP from Ottawa,Canada specializing in high availability,disaster recovery system infrastructures running on the Microsoft server technology stack.He is very passionate about technology but has interests in music,professional organizational development,leadership management matters when not working with databases.He lives up to his primary mission statement -“To help people and organizations grow and develop their full potential as God has planned for them."
Contact: http://rjssqlservernotes.wordpress.com/
A 20 year veteran of the IT industry with over 10 years experience as a software engineer Ron is a seasoned SQL Server performance optimization professional.Ron is currently supporting various clients as a consulting DBA specializing in PTO,Replication,HA/DR,and Security with Xtivia, Inc. a full-service IT company with offices in Dallas,TX, Colorado Springs,CO,and Edison,NJ.Ron earned a M.Sc. in Computer Science and a B.Sc. in Physics.Ron has 10 years of experience as an adjunct faculty member.
LinkedIn: Public Profile https://www.linkedin.com/in/andrewnovick
Contact: http://www.NovickSoftware.com
Andy Novick is a SQL Server MVP and consultant building business solutions with SQL Server. He has expertise in database design, T-SQL coding, SQL Server security, database performance tuning, partitioning, service broker, and database administration. Andy is a frequent speaker at local user group meetings and an author of two books on SQL Server.
Contact: http://weblogs.asp.net/sbchatterjee/default.aspx
Architect/Tech-lead in Hartford CT with over 20 years IT experience. Worked at companies like Aetna, IBM, Microsoft, UNICEF, United Technologies and State of Connecticut. Holds graduate degrees in Computer Science, Business Administration and Economics. Awarded the Microsoft MVP Award for SharePoint products 2008 thru 2013. He is active in the SharePoint StackExchange and other forums. Twitter: @sbc111 Acting Director - CT.NET Dev Group (CTDOTNET) CT Dev Startups Group (CTDEVSTARTUP).
Contact: http://sqlaj.wordpress.com/
AJ has over 14 years of experience working with a variety of databases. He has worked for military, civilian, and federal government organizations supporting a wide variety of applications. AJ is a frequent speaker at user groups, SQLSaturday#39;s, and PASS Virtual Chapters, and is a board member POSSE and CACTUSS. He is a PASS Programs Committee volunteer, and he loves being a part of the SQL Community.
LinkedIn: https://ca.linkedin.com/in/toddmcdermid
Contact: https://toddmcdermid.blogspot.com
Todd McDermid is a local BC developer who’s turned into a data warehouse and business intelligence evangelist. He started out programming DBase, VB6, and C# - but is now passionate about the SQL Server BI stack. He’s concentrated on using Integration Services to build the backbone of BI delivery – a dimensional warehouse. Todd has been known to blog, forum troll, code open-source extensions, and present on BI topics across the continent.
LinkedIn: http://www.linkedin.com/in/lennilobel
Contact: http://lennilobel.wordpress.com
Leonard Lobel (Microsoft MVP, Data Platform) is CTO and co-founder of Sleek Technologies, Inc., a New York-based development shop with an early adopter philosophy toward new technologies. He is also a principal consultant at Tallan, Inc., a Microsoft National Systems Integrator and Gold Competency Partner. Programming since 1979, Lenni specializes in Microsoft-based solutions, with experience that spans a variety of business domains, including publishing, financial, wholesale/retail, health care, and e-commerce. Lenni has served as chief architect and lead developer for various organizations, ranging from small shops to high-profile clients. He is also a consultant, trainer, and frequent speaker at local usergroup meetings, VSLive, SQL PASS, and other industry conferences. Lenni has also authored several MS Press books and Pluralsight courses on SQL Server programming.
Contact: http://www.infogoldusa.com
Steve Simon is a senior BI engineer with MyWebGrocer. He has been involved with database design and analysis for over 25 years. Steve has presented papers at eight PASS Summits and one at PASS Europe 2009 and 2010. He has just recently presented a Business Intelligence paper at Oracle Open World in San Francisco . Steve has also presented 5 papers at the Information Builders' (IBI) International Summits. He is a PASS regional mentor chair of the Oracle/SQL Server VC
Contact: http://bassplayerdoc.wordpress.com
Edwin Sarmiento is a SQL Server MVP from Ottawa,Canada specializing in high availability,disaster recovery system infrastructures running on the Microsoft server technology stack.He is very passionate about technology but has interests in music,professional organizational development,leadership management matters when not working with databases.He lives up to his primary mission statement -“To help people and organizations grow and develop their full potential as God has planned for them."
LinkedIn: https://www.linkedin.com/e/fpf/252170891
Contact: https://mvp.support.microsoft.com/profile=02C5CD07-7511-4151-A678-3A4A3451F85E
Bill Pearson created Island Technologies Inc. in 1997, and has developed a large and diverse customer base since. Bill#39;s background as a CPA, Internal Auditor, Management Accountant, and SQL Server MVP (BI) enables him to provide value to clients as a liaison between Accounting / Finance and Information Services. Bill has implemented enterprise business intelligence systems over the years for many Fortune 500 companies and focuses his practice upon the integrated Microsoft Business Intelligence
Contact: http://www.sqlha.com/blog/
Ben DeBow is a MDCBA, MCSE and MCITP focused on SQL Server consolidations, data architecture and performance tuning for organizations both large and small. Ben specializes in solving diverse and complex data and infrastructure challenges for large, global environments. Ben is a longtime member of the SQL community, volunteering the last 8 years as a SQLPass committee member, trainer and SQLPass presenter. Besides his work as a consultant, Ben is a cyclist, avid traveler and photographer.
LinkedIn: https://www.linkedin.com/in/brentozar
Contact: https://www.BrentOzar.com
Brent Ozar loves to make SQL Server faster. He created sp_Blitz and the SQL Server First Responder Kit. He shares what he's learned at BrentOzar.com.
Contact: http://www.KevinSGoff.net
Kevin S. Goff (http://www.kevinsgoff.net) is a Microsoft SQL Server MVP Database architect/developer/speaker/author Regular columnist for CoDe Magazine on .NET, SQL Server, and Business Intelligence topics Frequent speaker at community events in the Mid-Atlantic region. Host of BDBI Radio (http://www.bdbiradio.com), a weekly webcast on SQL/BI topics
Contact: http://aka.ms/sqlscott
Scott Klein is a senior consultant with SQL Solutions Group with over two decades of experience working with Microsoft SQL Server. Prior to SSG, Scott spent almost 10 years at Microsoft, traveling the globe as a technical evangelist training and speaking about SQL Server and Microsoft’s Azure data services. Scott’s recent focus has been on advanced analytics, including big data and IoT, providing real-world training to help bring intelligence to your data. Scott has authored several books focusing on data and data analytics. Scott is continuously striving and looking for ways to help developers and companies grok the wonderful world of data.
LinkedIn: https://www.linkedin.com/in/jasontomthomas
Contact: http://www.SqlJason.com
Jason Thomas is a Microsoft Certified SQL Server professional with over 10 years of Microsoft BI experience. He is a BI Consultant for BlueGranite, based in Charlotte, NC. When he#39;s not at work, Jason likes sharing his time between the MSDN forums (for which he was recognized with the Microsoft Community Contributor award), blogging about MSBI (www.SqlJason.com), speaking at SQL Server events, and watching movies with his wife (not necessarily in that order).
The following is a list of sponsors that helped fund the event.


Breaking News
Fenway Organist
Josh Kantor, organist for the Red Sox at Fenway, and librarian assistant at the Loeb Music Library, shares his experiences.
Josh Kantor, organist for the Red Sox at Fenway, and librarian assistant at the Loeb Music Library, shares his experiences.


--- layout: post status: publish published: true title: Opening Day 2011 author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 4672 wordpress_url: http://ivyenvy.com/?p=4672 date: '2011-04-01 05:56:48 +0000' date_gmt: '2011-04-01 10:56:48 +0000' categories: - Uncategorized - Ivy Envy - The Cubs - Events tags: - Alfonso Soriano - Aramis Ramirez - Carlos Zambrano - Kosuke Fukudome - Mike Quade - Podcast - Spring Training - Quad Cities - Twenty Sports Grille - Starlin Castro - Tyler Colvin - Minor Leagues - Game Chat - Andrew Cashner - Facebook - '2011' - We Believe - We Believe Documentary comments: - id: 3029 author: Ryan author_email<EMAIL_ADDRESS>author_url: '' date: '2011-04-01 14:34:22 +0000' date_gmt: '2011-04-01 19:34:22 +0000' content: "Answers:\r\n\r\n1) Let's hope so\r\n2) AAAAAAAAAAAAAAAAAARRRRRRRRRGHHHHHHHHHH!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! GATORADE COOLER DIE!!!\r\n3) I doubt it\r\n4) Yes. Absolutely.\r\n5) Probably...wait...Does Baltimore or Seattle count as \"another team\"?\r\n6) God I sure hope he's not a fluke. I hope the world for that kid. \r\n7) That's a joke, right?\r\n8) \ Of course he will. I think the question here is will he be able to make something out of that mesh? Ask my sister she's good with fabrics. \r\n\r\nMeehan" ---
The long winter is (kind of) over and baseball is back, Cubs fans. 2011 should be a real interesting season for the Cubs. We're happy to be cheering for the Cubs with you for another season. This season should answer a lot of questions for us.
* Is Starlin Castro going to continue to develop into the franchise player the Cubs are hoping he becomes?
* Is Carlos Zambrano going to get through a season without melting down?
* Will the Cubs be tempted to bring Aramis Ramirez back next year?
* Can Andrew Cashner become a solid starter?
* Can Fukudome get off to a hot start and the Cubs find another team interested in him?
* Was Tyler Colvin's rookie season a fluke and/or can he be the 1st baseman of the future?
* Will Soriano EVER be worth even half of his contract?
* Will Mike Quade be able to take this team and mesh the highly paid veterans with the new young players?
I'm looking forward to finding out the answers to these questions.
We have some new things for you this season. We launched our Game-Chat at the beginning of Spring Training. If you're watching a Cubs game and want to talk with some other fans, head over to our site and click on "Game Chat" underneath the header. It was a little slow in there during Spring Training, so if you checked it out and it was dead, understand that most people don't care too much about pre-season baseball.
We aim to bring you more coverage of the Cubs' minor league system in 2011. The Cubs have some talented young players in the system and we'll keep you up to date with their progress. We have started doing a weekly photo caption contest on our Facebook page and it's also become a pretty good place for conversation about the Cubs.
We will continue our monthly game-watches at Twenty Sports Grille in Moline. Our first is tomorrow, Saturday April 2nd. Our May game-watch will be May 2nd. It's a late west-coast game, but at 7pm, we'll be showing "We Believe", a documentary about the Cubs and Cubs fans. We are also well into the 3rd season of podcasting about the Cubs. The podcast will continue to come to you weekly and we're looking at including more interviews in 2011.
Enjoy the baseball this weekend. If you're in the Quad Cities, come on down to Twenty on Saturday, and.... GO CUBS!
Since it's Opening Day, I'll leave you with this:


001package com.github.tommyettinger.colorful.pure.cielab; 002 003import com.github.tommyettinger.colorful.pure.FloatColors; 004import com.github.tommyettinger.colorful.pure.Interpolations; 005import com.github.tommyettinger.colorful.pure.Interpolations.Interpolation; 006import com.github.tommyettinger.colorful.pure.MathTools; 007import com.github.tommyettinger.ds.FloatList; 008 009/** 010 * Static methods for handling gradients of smoothly-changing colors, typically inside of {@link FloatList}s. 011 * The intent is for the FloatList to be used as a sequence of packed float CIELAB colors. You can create a new 012 * FloatList gradient with {@link #makeGradient(float, float, int, Interpolation)}, but any FloatList will work 013 * (although it only makes sense if it contains packed float colors or is empty). Once you have a FloatList, you can 014 * pass it to {@link #appendGradient(FloatList, float, float, int, Interpolation)} to make a gradient between two 015 * colors, or {@link #appendGradientChain(FloatList, int, Interpolation, float...)} to make a gradient between more 016 * than two colors. You can also customize each section between colors with 017 * {@link #appendPartialGradient(FloatList, float, float, int, Interpolation)}, which is just like appendGradient() but 018 * doesn't add the end color (since it is the start color of the next partial gradient, until you finally end by 019 * appending just the end). Using appendPartialGradient(), you can have each transition use a different number of steps. 020 * <br> 021 * This class does some special handling for CIELAB colors. 022 */ 023public class GradientTools { 024 /** 025 * No need to instantiate. 026 */ 027 private GradientTools(){ 028 } 029 030 /** 031 * Creates a FloatList gradient from the packed float CIELAB color {@code start} to the packed float CIELAB color 032 * {@code end}, taking the specified number of steps and using linear interpolation. 033 * This limits individual steps of color to the correct CIELAB gamut, so even interpolations between colors at 034 * extreme points in the color space will stay in-gamut. 035 * @param start the packed float CIELAB color to start with 036 * @param end the packed float CIELAB color to end on 037 * @param steps how many steps the gradient should use; usually greater than 2, and must be non-negative 038 * @return a new FloatList that contains the requested gradient 039 */ 040 public static FloatList makeGradient(float start, float end, int steps) { 041 return makeGradient(start, end, steps, Interpolations.linear); 042 } 043 /** 044 * Creates a FloatList gradient from the packed float CIELAB color {@code start} to the packed float CIELAB color 045 * {@code end}, taking the specified number of steps and using the specified Interpolation for how it transitions. 046 * This limits individual steps of color to the correct CIELAB gamut, so even interpolations between colors at 047 * extreme points in the color space will stay in-gamut. 048 * @param start the packed float CIELAB color to start with 049 * @param end the packed float CIELAB color to end on 050 * @param steps how many steps the gradient should use; usually greater than 2, and must be non-negative 051 * @param interpolation a libGDX Interpolation that can be used to customize how start transitions to end 052 * @return a new FloatList that contains the requested gradient 053 */ 054 public static FloatList makeGradient(float start, float end, int steps, Interpolation interpolation) { 055 FloatList appending = new FloatList(steps); 056 if(steps <= 0) { 057 return appending; 058 } 059 if(steps == 1) { 060 appending.add(start); 061 return appending; 062 } 063 appendPartialGradient(appending, start, end, steps - 1, interpolation).add(end); 064 return appending; 065 } 066 067 /** 068 * Appends a gradient from the packed float CIELAB color {@code start} to the packed float CIELAB color {@code end}, 069 * taking the specified number of steps and using linear Interpolation for how it transitions. This limits 070 * individual steps of color to the correct CIELAB gamut, so even interpolations between colors at extreme points in 071 * the color space will stay in-gamut. 072 * @param appending a FloatList that will be appended to 073 * @param start the packed float CIELAB color to start with 074 * @param end the packed float CIELAB color to end on 075 * @param steps how many steps the gradient should use; usually greater than 2 076 * @return {@code appending}, after adding the gradient to the end 077 */ 078 public static FloatList appendGradient(FloatList appending, float start, float end, int steps) { 079 return appendGradient(appending, start, end, steps, Interpolations.linear); 080 } 081 /** 082 * Appends a gradient from the packed float CIELAB color {@code start} to the packed float CIELAB color {@code end}, 083 * taking the specified number of steps and using the specified Interpolation for how it transitions. This limits 084 * individual steps of color to the correct CIELAB gamut, so even interpolations between colors at extreme points in 085 * the color space will stay in-gamut. 086 * @param appending a FloatList that will be appended to 087 * @param start the packed float CIELAB color to start with 088 * @param end the packed float CIELAB color to end on 089 * @param steps how many steps the gradient should use; usually greater than 2 090 * @param interpolation a libGDX Interpolation that can be used to customize how start transitions to end 091 * @return {@code appending}, after adding the gradient to the end 092 */ 093 public static FloatList appendGradient(FloatList appending, float start, float end, int steps, Interpolation interpolation) { 094 if(appending == null) 095 return null; 096 if(steps <= 0) { 097 return appending; 098 } 099 if(steps == 1) { 100 appending.add(start); 101 return appending; 102 } 103 appending.ensureCapacity(steps); 104 appendPartialGradient(appending, start, end, steps - 1, interpolation).add(end); 105 return appending; 106 } 107 108 /** 109 * Appends a gradient between several packed float CIELAB colors provided in {@code chain}. This uses linear 110 * Interpolation for the whole gradient. Appends to the end of {@code appending} and produces a total of 111 * {@code steps} colors. 112 * @param appending a FloatList that will be appended to 113 * @param steps how many steps the gradient should use; usually greater than 2 114 * @param chain an array or varargs of packed float CIELAB colors that this will interpolate through in order 115 * @return {@code appending}, after adding the gradient to the end 116 */ 117 public static FloatList appendGradientChain(FloatList appending, int steps, float... chain) { 118 return appendGradientChain(appending, steps, Interpolations.linear, chain); 119 } 120 121 /** 122 * Appends a gradient between several packed float CIELAB colors provided in {@code chain}. This uses linear 123 * Interpolation for the whole gradient. Appends to the end of {@code appending} and produces a total of 124 * {@code steps} colors. 125 * @param appending a FloatList that will be appended to 126 * @param steps how many steps the gradient should use; usually greater than 2 127 * @param chain a FloatList of packed float CIELAB colors that this will interpolate through in order 128 * @return {@code appending}, after adding the gradient to the end 129 */ 130 public static FloatList appendGradientChain(FloatList appending, int steps, FloatList chain) { 131 return appendGradientChain(appending, steps, Interpolations.linear, chain); 132 } 133 134 /** 135 * Appends a gradient between several packed float CIELAB colors provided in {@code chain}. This uses the specified 136 * Interpolation for the whole gradient, which can make some colors use smaller sections than others. Appends to the 137 * end of {@code appending} and produces a total of {@code steps} colors. 138 * @param appending a FloatList that will be appended to 139 * @param steps how many steps the gradient should use; usually greater than 2 140 * @param interpolation a libGDX Interpolation that can be used to customize how start transitions to end 141 * @param chain a FloatList of packed float CIELAB colors that this will interpolate through in order 142 * @return {@code appending}, after adding the gradient to the end 143 */ 144 public static FloatList appendGradientChain(FloatList appending, int steps, Interpolation interpolation, FloatList chain) { 145 if (appending == null) 146 return null; 147 if(chain == null) 148 return appending; 149 if (steps <= 0 || chain.size() == 0) { 150 return appending; 151 } 152 if (steps == 1 || chain.size() == 1) { 153 appending.add(chain.first()); 154 return appending; 155 } 156 appending.ensureCapacity(steps); 157 int limit = steps - 1, splits = chain.size() - 1; 158 float step = 1f / steps, change = 0f; 159 for (int i = 0; i < limit; i++) { 160 float interp = interpolation.apply(change); 161 float splint = Math.min(Math.max(interp * splits, 0f), splits - 0.000001f); 162 int idx = (int)splint; 163 appending.add(ColorTools.limitToGamut(FloatColors.lerpFloatColors(chain.get(idx), chain.get(idx+1), MathTools.norm(idx, idx +1, splint)))); 164 change += step; 165 } 166 appending.add(chain.get(splits)); 167 return appending; 168 } 169 170 /** 171 * Appends a gradient between several packed float CIELAB colors provided in {@code chain}. This uses the specified 172 * Interpolation for the whole gradient, which can make some colors use smaller sections than others. Appends to the 173 * end of {@code appending} and produces a total of {@code steps} colors. 174 * @param appending a FloatList that will be appended to 175 * @param steps how many steps the gradient should use; usually greater than 2 176 * @param interpolation a libGDX Interpolation that can be used to customize how start transitions to end 177 * @param chain an array or varargs of packed float CIELAB colors that this will interpolate through in order 178 * @return {@code appending}, after adding the gradient to the end 179 */ 180 public static FloatList appendGradientChain(FloatList appending, int steps, Interpolation interpolation, float... chain) { 181 if (appending == null) 182 return null; 183 if(chain == null) 184 return appending; 185 if (steps <= 0 || chain.length == 0) { 186 return appending; 187 } 188 if (steps == 1 || chain.length == 1) { 189 appending.add(chain[0]); 190 return appending; 191 } 192 appending.ensureCapacity(steps); 193 int limit = steps - 1, splits = chain.length - 1; 194 float step = 1f / steps, change = 0f; 195 for (int i = 0; i < limit; i++) { 196 float interp = interpolation.apply(change); 197 float splint = Math.min(Math.max(interp * splits, 0f), splits - 0.000001f); 198 int idx = (int)splint; 199 appending.add(ColorTools.limitToGamut(FloatColors.lerpFloatColors(chain[idx], chain[idx+1], MathTools.norm(idx, idx +1, splint)))); 200 change += step; 201 } 202 appending.add(chain[splits]); 203 return appending; 204 } 205 206 /** 207 * Exactly like {@link #appendGradient(FloatList, float, float, int)}, but does not include 208 * {@code end} in what it appends to {@code appending}. This is intended for the implementation of chained 209 * gradients, where the end of a previous gradient becomes the start of the next one. This still uses the specified 210 * number of steps, it just doesn't append {@code end} in the last step. 211 * @param appending a FloatList that will be appended to 212 * @param start the packed float CIELAB color to start with 213 * @param end the packed float CIELAB color to end just before 214 * @param steps how many steps the gradient should use; usually greater than 2 215 * @return {@code appending}, after adding the gradient to its end 216 */ 217 public static FloatList appendPartialGradient(FloatList appending, float start, float end, int steps) { 218 return appendPartialGradient(appending, start, end, steps, Interpolations.linear); 219 } 220 /** 221 * Exactly like {@link #appendGradient(FloatList, float, float, int, Interpolation)}, but does not include 222 * {@code end} in what it appends to {@code appending}. This is intended for the implementation of chained 223 * gradients, where the end of a previous gradient becomes the start of the next one. This still uses the specified 224 * number of steps, it just doesn't append {@code end} in the last step. 225 * @param appending a FloatList that will be appended to 226 * @param start the packed float CIELAB color to start with 227 * @param end the packed float CIELAB color to end just before 228 * @param steps how many steps the gradient should use; usually greater than 2 229 * @param interpolation a libGDX Interpolation that can be used to customize how start transitions toward end 230 * @return {@code appending}, after adding the gradient to its end 231 */ 232 public static FloatList appendPartialGradient(FloatList appending, float start, float end, int steps, Interpolation interpolation){ 233 if(appending == null) 234 return null; 235 if(steps <= 0) { 236 return appending; 237 } 238 if(steps == 1) { 239 appending.add(start); 240 return appending; 241 } 242 int limit = steps; 243 float step = 1f / steps, change = 0f; 244 for (int i = 0; i < limit; i++) { 245 appending.add(ColorTools.limitToGamut(FloatColors.lerpFloatColors(start, end, interpolation.apply(change)))); 246 change += step; 247 } 248 return appending; 249 } 250}


APT PUPIL Cast: Ian McKellan, Brad Renfro, Bruce Davison, Elias Koteas, Joe Morton, David Schwimmer Director: Bryan Singer Screenplay: Brandon Boyce based on the novella by Stephen King Reviewed by Luke Buckmaster
On the Buckmaster scale of 0 stars (bomb), to 5 stars (a masterpiece): 3 and a half stars
Standard horror films keep characters and their actions in check. They produce shrieks and squeals from violence that is either meaningless or irrelevant, and rarely look at what motives evil actions. It is sort of an irony that Stephen King - whom you may expect would produce this sort of stuff - wrote the novella on which Apt Pupil is based. Brandon Boyce has skillfully adapted King's work and made it accessible for the big screen, while director Brian Singer (who astonished audiences with The Usual Suspects) and the film's performers give it impact. The result is a subversive and gripping experience; one that crawls under your skin and stays there. Sometimes disturbing, at other times merely entertaining, this is a solid piece that grounds itself in a truly frightening subject matter, but occasionally deviates into ordinary urban scenarios.
Todd Bowden (Brad Renfro) is an apt pupil. He is a straight A's student who is destined to top his class. After a week of learning about the Holocaust, Todd is fascinated - so much so that he immerses himself in extra-curriculum study of the era. In his research, he discovers an incredible secret that nobody else has: Nazi war criminal Kurt Dussander (Sir Ian McKellen) has been quietly living in Todd's hometown under the assumed name of Arthur Denker. Denker has lived a quiet, uneventful life - until now. Todd confronts Denker and blackmails him with a deal he can't refuse - Todd will keep silent about his true identity, and in return Denker must tell him about the atrocities he committed in the war. Thus a dangerous relationship begins, in which Todd learns valuable lessons about having the upper hand.
The character of Kurt Dussander is one of the most fascinating in recent years. His fragile elderly body is deceiving, as is his serene existence. As Todd unlocks Dussander's memories, he also unlocks the man's true character - his sinister actions have obviously only been in hibernation. Sir Ian McKellen brings Dussander to life with eerie skill, and Brad Renfro is also great as a teenager whose world is turned topsy-turvy. McKellen and Renfro first appear to be a hostile odd couple, but as the plot goes along Singer draws parallels. There is no hero in this story, nor is there a bad guy.
The film's most chilling moments are when we learn of Dussander's dark past. In one scene he explains in explicit detail what the gassing chambers were like - though it is purely dialogue, a painful visual illustration is carved. Had the film followed this rapid psychological momentum, it may have been a mind-rousing classic. But Singer deviates too often from his exhilarating central plot. In comparison to the nightmares of war told by one of its fomenters, the slip of Todd's school grades seems woefully uninspired.  Apt Pupil is a must see for anybody who ever thought a horror film can't have a brain or a heart. Though far from perfect, this film evokes a morbid fascination that is hard to shake.
Read more of my reviews at In Film Australia http://infilmau.iah.net
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


--- layout: page status: publish published: true title: 1977 1 Meter Black and White DOQs (Salt Lake County Only) author: display_name: Rick Kelson login: rkelson email<EMAIL_ADDRESS>url: '' author_login: rkelson author_email<EMAIL_ADDRESS>wordpress_id: 841 wordpress_url: http://gis.utah.gov/?page_id=841 date: '2011-08-15 17:13:22 -0600' date_gmt: '2011-08-15 17:13:22 -0600' categories: [] tags: - aerial photography - sgid - Data - utah - gis - map - mapping - dataset - download - agrc - layer - metadata - digital - geographic - information - database - state - statewide - imagery - 1 meter - DOQ - '1977' ---
AGRC has a complete 1-meter Black and White Salt Lake County DOQ coverage from 1977. The DOQs are available as single quads and also as a Mr.Sid county mosaic. The Salt Lake County 1977 DOQs are in a UTM NAD83 projection.
If you have any trouble contact Rick Kelson at<PHONE_NUMBER>).


Stripe Checkout Demo
English language, wallets, and cards.
German language, wallets, and cards.
Dutch language, wallets, cards, and iDEAL.
Malay language, wallets, and cards.
French language, wallets, and cards.
Polish language, wallets, and cards.


What is the weather like?
The weather is typically sunny and the temperate averages 61° F yearly.
Is there parking available downtown?
There are more than 800 free street parking spots as well as 14 parking facilities within walking distance. Simply follow the green "P"
How can I ride the Trolley?
The trolley does not have a fare and is operational Thursdays and Fridays from 6-11 p.m., Saturdays from 10 a.m. to 11 p.m. and Sundays from 1-8 p.m.
What are the bike lockers?
Bike lockers offer renters a safe way to secure their bikes. Rental terms are $50 for six months.
Where can I find more information?
More information can be found at greenvillesc.gov .


22.2.3. Model
Parameters – Multi Perceptron
Key
values:
·
Provide various advanced machine
learning methods to deal with different types of geological settings
·
Robust algorithms implemented by
machine learning experts
·
Flexible in configuring model inputs
and architectures
·
Workflow interface à easy to use and adjust
·
Able to build many models at the same
time à easy to compare
and select the most appropriate methods
·
Maximize user’s control capacity by
allowing them to adjust several advanced parameters
·
Offer different ways to assess
training and predicting capacity: training/loss error/accuracy cross-plot as
well as a confusion matrix
Machine
Learning (ML) Tool Kit in the i2G platform is an advanced tool that offers many
state-of-the-art algorithms in the industry. They are divided into 2 groups,
namely Regression and Classification.
Fundamentally,
classification is about predicting a label (discrete properties such as facies)
and regression is about predicting a quantity (continuous properties such as
permeability).
Before
running any ML technique, the user is required to create a ML model:
Step 1. Go to “Machine Learning” tab
Figure 22‑1 Machine learning tab on Menu Bar
Step 2. Select the “Regression Model” or “Classification Model” to make a new model. If the user wants to open an existing model, select “Open Model”
Step 3. Fill in “Model name” if a new model is being created
Figure 22‑2 New model dialog
When
the user selects “Regression” in the model spec, i2g will direct to a window
where the user can define the input:
Step 1. Highlight the curves/Family/Main Family
Figure 22‑3 Family selection
Step 2. Click on the “Input curve or Target Output” to select the curves. “Target output” is the one you wish to predict and is hard data for training such as core permeability. The user can search for the desired curves/family in the search window
Figure 22‑4 Select input curves
Tip:
make sure your inputs are normalized and properly
corrected for bad hole effects
Step 3. Define input/output curve transformation (linear/logarithm/exponential)
Figure 22‑5 Define input/output curve transformation
Figure 22‑6 Define plots name
Tip:
in order to generate a robust model, your training
data in “curves output” should cover all the data space – has samples in both
good and poorer reservoir quality intervals
In
this tab, the user can select various advance ML algorithms, including 1-Linear Regression, 2-Huber Regression, 3-Lasso (least absolute shrinkage and
selection operator), 4-Decision tree,
5-Random Forest, 6-Support Vector Machine and 7-Multilayer Perceptron
Each
ML method will have different settings which are shown in the next slides
Figure 22‑7 Setting model information
Tips: The user can try out many different algorithms
with full control over the input parameters
Multi Perceptron is a class of
feedforward artificial neural network. An MLP consists of three types of layers
of nodes, including an input layer, hidden layers, and an output layer. Except
for the input nodes, each node is a neuron that uses a nonlinear activation
function. MLP can be used for both classification and regression problems. The
supervised learning technique utilized for MLP is the backpropagation algorithm
Figure 22‑8 Select Multi Perceptron model
Input parameters
Input parameters
for this model are defined as follows:
Activation: is
the name of the activation function(s) for hidden nodes
·
‘Logistic’,
the logistic sigmoid function, returns f(x) = 1 / (1 + exp(-x)).
·
‘Tanh’,
the hyperbolic tan function, returns f(x) = tanh(x).
·
‘Relu’,
the rectified linear unit function, returns f(x) = max(0, x), Maximum
Iteration: is the maximum number of iterations. Unless the training model
converges at some point during the training process, which is determined by
“Tol” parameter, it will stop when the number of iterations exceeds Max_iter.
Figure 22‑9 Multi Perceptron model information
·
Tol:
Tolerance for optimization. When the loss or score is not improving by at least
two consecutive iterations, convergence is considered to be reached and
training stops.
·
Initial
Learning Rate: It controls the step-size in updating the weights.
Tip: Advanced parameters
that can be adjusted in case the normal ones are not capable of generating the
desired output
Network Structure
Users
can design their model architecture by typing the number of hidden layers
(“Hidden_layer_sizes”) and the number of nodes in a layer (“layer 0”/”layer 1”)
depending on how complex their data are.
The
model architecture is visualized by the window on the right and is
automatically updated when changed.
When the user wants to eliminate any input nodes (curves): click on the node
Figure 22‑10 design model architecture
Input Data – Training
In this tab, the user can drag and drop any dataset into “train”, “verify” and “predict” window. Make sure that this dataset contains all input curves/families defined in the “SELECTION CURVE” step.
Figure 22‑11 drag and drop datasets into Train, Verify
and Predict window
This filter option enables the user to select the best data to input into the training process which will allow us to generate a robust trained model
Figure 22‑12 Filter input data for training
Training/ Validation loss
This
plot allows the user to assess the output model by looking at the “training
loss” and “validation loss” lines which are calculated at every iteration.
20%
of the entire data is left out and are not put into the training process. These
points are used for constructing the “validation loss” line. This is done so
that the user can avoid overfitting problems as shown in the plot on the right
Mean
Square Errors:
Figure 22‑13 Training/ Validation loss plot
Verify
In this part, the user can see what are
the actual results after minimizing the training and validation errors. The
access to the plot is located at the bottom of the window as shown below
Figure 22‑14 Verify the model
Predict
After the user is happy with the
training and verify parts, they can apply the trained model to many other
datasets to predict the desired property
Figure 22‑15 Predict the desired property
Tip: the model is automatically saved and will be
over-written when being run next time so make sure not to edit anything if you
want to keep the trained model.
FZI prediction
Figure 22‑16 FZI prediction plot
Method: Multi Perceptron
Figure 22‑17 Method Multi Perceptron
Permeability prediction
Figure 22‑18 Permeability prediction plot
This
step is similar to what is required in regression. The only difference is the
“curve output” should be a discrete property such as facies
Figure 22‑19 Curve selection in Classification model
Seven
learning algorithms are offered in this module, including 1-Decision Tree, 2- KNN, 3-Logistic Regression,
4-Random Forest, 5- Neural Net, 6-Self Organizing Map (SOM)
and 7-HIMFA
Figure 22‑20 Parameters in Classification model
Neural Network Classifier:
Neural Network Classifier
is a multilayer perceptron network for
classification problems. This model optimizes the log-loss function using LBFGS
or stochastic gradient descent. Input parameters for this model are defined as
follows.
·
Activation:
is the name of the activation function for hidden layers.
·
Algorithm:
is the name of the training algorithm, which is either a backpropagation or
evolution strategy algorithm.
·
The backpropagation algorithm
works best with many epochs.
·
The evolution algorithm is preferable with a smaller number of
epochs, about 1000.
·
Batch_size:
Number of samples per gradient update. If batch_size =0, the number of training
samples will be used.
·
Learning_rate: It controls the step-size in updating the
weights.
·
Num_epochs:
maximum number of training iterations.
·
Optimizer:
is the solver for weight optimization.
·
Warm-up:
is to determine the initial values of weights. When set to True, the model will
run with batch_size = 1 and num_epochs = 1 to get the initial weights,
otherwise, it just randomizes the initial weights. After this process, the
model will run the training process as set by other parameters.
·
Boosting_ops:
this parameter is only used for the evolution algorithm. This parameter
determines the number of times that the weights are further updated based on
the accuracy after the training process based on the loss function finishes.
The default is 100.
·
Sigma:
this parameter is only used for the evolution algorithm. This parameter
determines the variance size of the Gaussian distribution used for randomizing
the weights.
·
Population:
is the number of sets of randomized weights for each epoch. This parameter is
only used for the evolution algorithm.
Figure 22‑21 Neural Network Classifier model information
Figure 22‑22 Neural Network Classifier model architecture
Tip: Adding more
layers/nodes is useful when it comes to dealing with a more complicated dataset
Again, this tab contains train – verify –
predict as it does in regression. For classification i2g also provides a
“confusion matrix” to assist the user in checking the accuracy of their training
model for discrete properties
Figure 22‑23 Plots in Classification model
Tip: For discrete
properties, try to input an equal number of samples for each class
Neural Network Classifier –
Confusion matrix
Comparison
between the predicted classes and the true labels (hard data for training).
This matrix utilizes data from the validation set
Figure 22‑24 Neural Network Classifier – Confusion matrix
Figure 22‑25 Verify plot in Classification model
Figure 22‑26 Flow Unit prediction


@import model.{InvalidEmail, OtherError, NonsuccessResult}
@(result: NonsuccessResult)
@result match {
case InvalidEmail => {
@fragments.inlineSvg("cross", "icon")
Invalid email address
Sorry, we couldn't verify that email address. Please try again or contact user help.
}
case OtherError => {
@fragments.inlineSvg("cross", "icon")
Subscription error
Sorry, there was a problem with your subscription request. Please try again or contact user help.
}
}


announcement Not currently accepting students
I consider teaching on of the most important things I do as a cellist, and by far the one that holds the most responsibility.
I love teaching, and my students love coming to lessons. I have developed a unique teaching style since I started teaching in 2004 which is tailored to each student. I do not hold strictly to "Suzuki" "Traditional" or "Starker" pedagogies; I take what I like best from what I have learned and pass it on.


13.94. Release 0.168
General Changes
- Fix correctness issues for certain
JOIN
queries that require implicit coercions
for terms in the join criteria.
- Fix invalid “No more locations already set” error.
- Fix invalid “No more buffers already set” error.
- Temporarily revert empty join short-circuit optimization due to issue with hanging queries.
- Improve performance of
DECIMAL
type and operators.
- Optimize window frame computation for empty frames.
json_extract()
and json_extract_scalar()
now support escaping double
quotes or backslashes using a backslash with a JSON path subscript. This changes
the semantics of any invocation using a backslash, as backslashes were previously
treated as normal characters.
- Improve performance of
filter()
and map_filter()
lambda functions.
- Add Memory Connector.
- Add
arrays_overlap()
and array_except()
functions.
- Allow concatenating more than two arrays with
concat()
or maps with map_concat()
.
- Add a time limit for the iterative optimizer. It can be adjusted via the
iterative_optimizer_timeout
session property or experimental.iterative-optimizer-timeout
configuration option.
ROW
types are now orderable if all of the field types are orderable.
This allows using them in comparison expressions, ORDER BY
and
functions that require orderable types (e.g., max()
).
JDBC Driver Changes
- Update
DatabaseMetaData
to reflect features that are now supported.
- Update advertised JDBC version to 4.2, which part of Java 8.
- Return correct driver and server versions rather than
1.0
.
Hive Changes
- Fix reading decimals for RCFile text format using non-optimized reader.
- Fix bug which prevented the file based metastore from being used.
- Enable optimized RCFile reader by default.
- Common user errors are now correctly categorized.
- Add new, experimental, RCFile writer optimized for Presto. The new writer can be enabled with the
rcfile_optimized_writer_enabled
session property or the hive.rcfile-optimized-writer.enabled
Hive catalog property.
Cassandra Changes
- Add predicate pushdown for clustering key.
MongoDB Changes
- Allow SSL connections using the
mongodb.ssl.enabled
config flag.
SPI Changes
- ConnectorIndex now returns
ConnectorPageSource
instead of RecordSet
. Existing connectors
that support index join can use the RecordPageSource
to adapt to the new API.


About Me
My name is Brian Warner, and I am currently beginning my career in the area of coding and web development. I was born and raised in Atlanta and proceeded to receive my degree in political science from Amherst College. From then on I primarily worked in the area of fine dining and front of house management. I currently have my compTIA certifications in A+, Network+, and Security+ and working through Georgia Tech's full-stack web development and coding bootcamp.
Example Project: Creative Meet!
Link for Heroku Deployment for Creative Meet
Example Project: Eat-Da-Burger!
Link for Heroku Deployment for Eat-Da-Burger
Link to Deployed Application for Read More TV Project
Example Project: Template Engine-Employee Summary
Link Project: Template Engine-Employee Summary
Example Project: Password Generator
Link to Deployed Application for Password Generator
Example Project: Weather Dashboard


0.4.0
Constructs a confusion matrix
(Array<any>)
Labels of the confusion matrix, a 1D Array
const CM = new ConfusionMatrix([[13, 2], [10, 5]], ['cat', 'dog'])
Construct confusion matrix from the predicted and actual labels (classes). Be sure to provide the arguments in the correct order!
(Array<any>)
The predicted labels of the classification
(Array<any>)
The actual labels of the classification. Has to be of same length as
predicted.
ConfusionMatrix
:
Confusion matrix
Compute the general prediction accuracy
number
:
The prediction accuracy (
[0-1]
F1 score https://en.wikipedia.org/wiki/F1_score
(any)
The label that should be considered "positive"
number
:
False discovery rate (FDR) https://en.wikipedia.org/wiki/False_discovery_rate
(any)
The label that should be considered "positive"
number
:
False negative rate a.k.a. miss rate. https://en.wikipedia.org/wiki/Type_I_and_type_II_errors#False_positive_and_false_negative_rates
(any)
The label that should be considered "positive"
number
:
False positive rate a.k.a. fall-out rate. https://en.wikipedia.org/wiki/Type_I_and_type_II_errors#False_positive_and_false_negative_rates
(any)
The label that should be considered "positive"
number
:
Informedness https://en.wikipedia.org/wiki/Youden%27s_J_statistic
(any)
The label that should be considered "positive"
number
:
Matthews correlation coefficient (MCC) https://en.wikipedia.org/wiki/Matthews_correlation_coefficient
(any)
The label that should be considered "positive"
number
:
Negative predictive value https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values
(any)
The label that should be considered "positive"
number
:
Get the positive predictive value a.k.a. precision. Computes TP / (TP + FP) https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values
(any)
The label that should be considered "positive"
number
:
Get the true negative rate a.k.a. specificity. Computes the ration between the number of true negative predictions and the total number of negative samples. https://en.wikipedia.org/wiki/Sensitivity_and_specificity
(any)
The label that should be considered "positive"
number
:
Get the true positive rate a.k.a. sensitivity. Computes the ratio between the number of true positive predictions and the total number of positive samples. https://en.wikipedia.org/wiki/Sensitivity_and_specificity
(any)
The label that should be considered "positive"
number
:
The true positive rate
[0-1]


Back up your Github repositories locally.
To install it as a Gem, just run:
$ gem install github-backup
To use it:
$ github-backup ddollar /path/to/my/backup/root
You will need a ~/.gitconfig
file in place with a
[github]
section
See: http://github.com/guides/tell-git-your-user-name-and-email-address
If you don’t have a [github]
section set up in your
~/.gitconfig
file, you can provide your user name and Github
API at the command line.
MIT License
Created by David Dollar
Patches contributed by: Gabriel Gilder
Copyright (c) 2010 David Dollar.


spoonacular Taste Visualizer
Create an informative and attractive taste visualization of a recipe.
Ingredients
Preview Taste Visualizer
powered by
spoonacular API