Calculate multiple results by using a data table. Data tables are part of a suite of commands that are called what- if analysis tools. When you use data tables, you are doing what- if analysis.

Terminology and overview. Formally, a "database" refers to a set of related data and the way it is organized. Access to this data is usually provided by a "database. Brent Ozar Unlimited's specialized experts focus on your goals, diagnose your tough database pains, and make Microsoft SQL Server faster and more reliable. How to use Oracle INSERT, UPDATE, DELETE, MERGE, Multi INSERT Statements with Examples. Interactive SQL documentation for SAP Adaptive Server Enterprise: Interactive SQL Online Help Interactive SQL Version 16.0. There are two ways to update statistics. The first way is the easy way. It is one line of code that will update all the statistics in the database using the default.

What- if analysis is the process of changing the values in cells to see how those changes will affect the outcome of formulas on the worksheet. For example, you can use a data table to vary the interest rate and term length that are used in a loan to determine possible monthly payment amounts. Kinds of what- if analysis    There are three kinds of what- if analysis tools in Excel: scenarios, data tables, and goal seek. Scenarios and data tables take sets of input values and determine possible results. Goal Seek works differently from scenarios and data tables in that it takes a result and determines possible input values that produce that result. Like scenarios, data tables help you explore a set of possible outcomes. Unlike scenarios, data tables show you all the outcomes in one table on one worksheet.

Using data tables makes it easy to examine a range of possibilities at a glance. Because you focus on only one or two variables, results are easy to read and share in tabular form.

Database Terminology is explained in this comprehensive list of definitions. We gathered 145 of the top database terms and defined them in this post. Requirements summary. In this test, each request is processed by fetching multiple rows from a simple database table and serializing these rows as a JSON response.

A data table cannot accommodate more than two variables. If you want to analyze more than two variables, you should instead use scenarios. Although it is limited to only one or two variables (one for the row input cell and one for the column input cell), a data table can include as many different variable values as you want. A scenario can have a maximum of 3.

For information about what- if analysis, see Introduction to What- If Analysis. Data table basics. You can create one- variable or two- variable data tables, depending on the number of variables and formulas that you want to test. One- variable data tables    Use a one- variable data table if you want to see how different values of one variable in one or more formulas will change the results of those formulas. For example, you can use a one- variable data table to see how different interest rates affect a monthly mortgage payment by using the PMT function. You enter the variable values in one column or row, and the outcomes are displayed in an adjacent column or row.

In the following illustration, cell D2 contains the payment formula, =PMT(B3/1. B4,- B5), which refers to the input cell B3.

Two- variable data tables    Use a two- variable data table to see how different values of two variables in one formula will change the results of that formula. For example, you can use a two- variable data table to see how different combinations of interest rates and loan terms will affect a monthly mortgage payment. In the following illustration, cell C2 contains the payment formula, =PMT(B3/1. B4,- B5), which uses two input cells, B3 and B4.

Data table calculations    Data tables are recalculated whenever a worksheet is recalculated, even if they have not changed. To speed up calculation of a worksheet that contains a data table, you can change the Calculation options to automatically recalculate the worksheet but not the data tables.

See the section Speed up calculation in a worksheet that contains data tables.

Tech. Empower Framework Benchmarks. In the following tests, we have measured the performance of several web application platforms, full- stack frameworks, and micro- frameworks (collectively, . Results are captured on Amazon EC2 and on physical hardware. The test implementations are largely community- contributed and all source is available at the Git.

Hub repository. Note: We're using the word . The Dell R7. 20xd servers in this new environment feature dual Xeon E5- 2. Round 8 — Six more frameworks contributed by the community takes the total count to 9.

While comparatively easy to measure, performance is frequently given little consideration. We hope to help change that. Application performance can be directly mapped to hosting dollars, and for companies both large and small, hosting costs can be a pain point. Weak performance can also cause premature and costly scale pain by requiring earlier optimization efforts and increased architectural complexity. Finally, slow applications yield poor user experience and may suffer penalties levied by search engines. What if building an application on one framework meant that at the very best your hardware is suitable for one tenth as much load as it would be had you chosen a different framework?

The differences aren't always that extreme, but in some cases, they might be. Especially with several modern high- performance frameworks offering respectable developer efficiency, it's worth knowing what you're getting into.

Terminologyframework. We use the word framework loosely to refer to any HTTP server implementation upon which you could build a web application—a full- stack framework, a micro- framework, or even a web platform such as Rack, Servlet, or plain PHP. For us, platforms are broadly defined as anything situated between the programming language and the web framework (examples are Servlet, Netty, and Rack). Please let us know how we can fix it, or submit a Git.

Hub pull request, so we can get it right. We've done so because it's of interest to us. You can consider it a stand- in for any relatively lightweight minimal- locking Java framework. While we're proud of how it performs among the well- established field, this exercise is not about Gemini. Even better, craft the test implementation yourself and submit a Git.

Hub pull request so we can get it in there faster! With so many frameworks we have a never- ending game of whack- a- mole. If you think an update will affect the results, please let us know (or better yet, submit a Git.

Hub pull request) and we'll get it updated! Cache tests are planned for later rounds.

However, curiously, in spot tests, some frameworks paired with Memcached were conspicuously slower than other frameworks directly querying the authoritative My. SQL database (recognizing, of course, that My.

SQL had its entire data- set in its own memory cache). For simple . We hope to in the future! However, as with test durations, we intend to increase the duration of the warmup when we have a continuously- running test environment. Environment. Apache. Bench remains a single- threaded tool, meaning that for higher- performance test scenarios, Apache. Bench itself is a limiting factor. Wrk is a multithreaded tool that provides a similar function, allowing tests to run for a prescribed amount of time (rather than limited to a number of requests) and providing us result data including total requests completed and latency information.

Selecting EC2 as a platform also allows the tests to be readily verified by anyone interested in doing so. However, we've also executed tests on our Core i.

Sandy Bridge) workstations running Ubuntu as a non- virtualized comparison. Doing so confirmed our suspicion that the ranked order and relative performance across frameworks is mostly consistent between EC2 and physical hardware. That is, while the EC2 instances were slower than the physical hardware, they were slower by roughly the same proportion across the spectrum of frameworks. Why aren't you using Tomcat for the Java frameworks? The GPL version that we used for our tests is a relatively lightweight Servlet container.

We tested on Tomcat as well but ultimately dropped Tomcat from our tests because Resin was slightly faster across all Servlet- based frameworks. Every test is preceded by a warmup and brief (several seconds) cooldown prior to gathering test data.

Results. Assuming proper response headers are provided, at approximately 2. The test tool changed at Round 2 and some framework IDs were changed at Round 3. As a result, the results.

Rounds 1 and 2 would have required manual editing and we opted to simply remove the previous rounds from this site. You can still see those rounds at our blog: Round 1, Round 2. Do you accept early builds of frameworks or toy projects? The goal is approximating a sensible production deployment as accurately as possible.

We also want this project to be as transparent as possible, so we have posted our test suites on Git. Hub. Environment details. Server. Central. Physical hardware environment for Rounds 1.

If you have any corrections or contributions, please submit a pull request! Forum / mailing list. Join the conversation about this project on the framework- benchmarks Google Group. Atlantis Mysteries Of Ancient Inventors Setup Outlook. Test requirements. We invite fans of frameworks and especially authors or maintainers of frameworks to join us in expanding the coverage of this project by implementing tests and contributing to the Git. Hub repository. We expect the Server header to be whatever is normal for the platform or framework. It is not acceptable to use batches.

It is not acceptable to execute multiple SELECTs within a single statement. It is not acceptable to retrieve all required rows using a SELECT .. WHERE id IN (..) clause. Each World object must be added to a list or array. The list or array must be serialized to JSON and sent as a response. The response content type must be set to application/json.

This confirms that the data structure is dynamic- sized. The new fortune is not persisted to the database; it is ephemeral for the scope of the request. The new Fortune's message must be .

No ORDER BY clause is permitted in the database query (ordering within the query would be of negligible value anyway since a newly instantiated Fortune is added to the list prior to sorting). The sorted list must be provided to a server- side template and rendered to simple HTML (see below for minimum template). The resulting HTML table displays each Fortune's id number and message text.

This test does not include external assets (CSS, Java. Script); a later test type will include assets. The HTML generated by the template must be sent as a response. Be aware that the message text fields are stored as UTF- 8 and one of the fortune cookie messages is in Japanese.

The resulting HTML must be delivered using UTF- 8 encoding. The Japanese fortune cookie message must be displayed correctly.

Be aware that at least one of the message text fields includes a < script> tag. The server- side template must assume the message text cannot be trusted and must escape the message text properly. The implementation is encouraged to use best practices for templates such as layout inheritence, separate header and footer files, and so on. However, this is not required. We request that implementations do not manage assets (Java. Script, CSS, images). We are deferring asset management until we can craft a more suitable test.

The response content type must be set to text/html. The response headers must include either Content- Length or Transfer- Encoding. The response headers must include Server and Date. Use of an in- memory cache of Fortune objects or rows by the application is not permitted. Use of prepared statements for SQL database tests (e.

My. SQL) is encouraged but not required. Server support for HTTP Keep- Alive is strongly encouraged but not required. If HTTP Keep- Alive is enabled, no maximum Keep- Alive timeout is specified by this test. The request handler will be exercised at concurrency levels ranging from 8 to 2. The request handler will be exercised using GET requests.

Example request. GET /fortunes HTTP/1. User- Agent: Mozilla/5. X1. 1; Linux x. 86.

It is not acceptable to change the random. Number value of all rows to the same random number using an UPDATE .. WHERE id IN (..) clause. Each World object must be added to a list or array. The list or array must be serialized to JSON and sent as a response. The response content type must be set to application/json.