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Lead , Lag ,  First Value , Last Value ,  Keep First , Keep Last | Oracle SQL Tutorial | Mr.Murali
 
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Lead , Lag , First Value , Last Value , Keep First , Keep Last in Oracle SQL | Oracle SQL Tutorial | Mr.Murali ►For Registration : https://goo.gl/r6kJbB ►Call: +91-8179191999 ► Visit Our Website: http://nareshit.in/ http://nareshit.com/ ► About NareshIT: "Naresh IT is the Best Software Training Institute for Hadoop, Salesforce, AWS, DevOps, Sprak, Data Science, Python, Tableau, RPA ,Java, C#.NET, ASP.NET, Oracle, Testing Tools, Silver light, Linq, SQL Server, Selenium, Android, iPhone, C Language, C++, PHP and Digital Marketing in Hyderabad, Chennai and Vijayawada, India which provides online and classroom training classes" ►For Registration : https://goo.gl/r6kJbB ►Call: India- 8179191999, USA- 404-232-9879 Email: [email protected] ►Our Online Training Features: 1.Training with Real-Time Experts 2.Industry Specific Scenario’s 3.Flexible Timings 4.Soft Copy of Material 5.Share Video's of each and every session. Check The Below Links: ►For Course Reg : https://goo.gl/r6kJbB ► Subscribe to Our Channel: https://goo.gl/q9ozyG ► Circle us on G+: https://plus.google.com/NareshIT ► Like us on Facebook: https://www.facebook.com/NareshIT ► Follow us on Twitter: https://twitter.com/nareshitech ► Visit Our Website: http://nareshit.in/ http://nareshit.com/
Views: 13679 Naresh i Technologies
LAG and LEAD in SQL | Oracle SQL Tutorial Videos | Mr.Vijay Kumar
 
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LAG and LEAD in SQL | Oracle SQL Tutorial Videos | Mr.Vijay Kumar ** For Online Training Registration: https://goo.gl/r6kJbB ► Call: +91-8179191999 💡 Visit Our Website for Classroom Training: https://nareshit.in/oracle-training/ 💡 For Online Training: https://nareshit.com/oracle-online-training/ #Oracle #Training #CourseVideos -------------------------- 💡 About NareshIT: "Naresh IT is having 14+ years of experience in software training industry and the best Software Training Institute for online training, classroom training, weekend training, corporate training of Hadoop, Salesforce, AWS, DevOps, Spark, Data Science, Python, Tableau, RPA , Java, C#.NET, ASP.NET, Oracle, Testing Tools, Silver light, Linq, SQL Server, Selenium, Android, iPhone, C Language, C++, PHP and Digital Marketing in USA, Hyderabad, Chennai and Vijayawada, Bangalore India which provides online training across all the locations -------------------------- 💡 Our Online Training Features: 🎈 Training with Real-Time Experts 🎈 Industry Specific Scenario’s 🎈 Flexible Timings 🎈 Soft Copy of Material 🎈 Share Videos of each and every session. -------------------------- 💡 Please write back to us at 📧 [email protected]/ 📧 [email protected] or Call us at the USA: ☎+1404-232-9879 or India: ☎ +918179191999 -------------------------- 💡 Check The Below Links ► For Course Reg: https://goo.gl/r6kJbB ► Subscribe to Our Channel: https://goo.gl/q9ozyG ► Circle us on G+: https://plus.google.com/+NareshIT ► Like us on Facebook: https://www.facebook.com/NareshIT ► Follow us on Twitter: https://twitter.com/nareshitek ► Follow us on Linkedin: https://goo.gl/CRBZ5F ► Follow us on Instagram: https://goo.gl/3UXYK3
Views: 11401 Naresh i Technologies
Analytical Functions in oracle explained with real examples
 
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This video explains analytical functions and how they are implemented in real projects. Analytical functions are somewhat similar to aggregate functions,but they offer much more. Why use analytical function ? They allow you to write fast and concise queries which otherwise will involve self join and long processing times They allow you to perform aggregate functions independently on sets of partitions. You can access values from previous rows in current row and you can restrict the window on which you want to apply this analytical function. I have given additional practice exercises along with the dataset so that you can comfortably work with analytical functions. You can find the sample problems along with dataset in the below link. http://www.internshipsfromhome.com/oracle-analytical-functions-ddl-and-dml/
Views: 24896 Tech Coach
Oracle Analytical functions Sum , Lead , Lag and Avg
 
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This video tutorial explains Oracle Analytical functions further continuing from my previous video. We demonstrate practical usage of these functions with examples. For Software used in the video refer : www.querylight.in
Views: 3061 Query Light
Oracle Performance Tuning - Lead and Lag
 
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A brief overview about Lead and Lag analytic function in Oracle
Views: 1411 Saurabh Kumar
Lead and Lag functions in SQL Server 2012
 
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In this video we will discuss about Lead and Lag functions. Lead and Lag functions Introduced in SQL Server 2012 Lead function is used to access subsequent row data along with current row data Lag function is used to access previous row data along with current row data ORDER BY clause is required PARTITION BY clause is optional Syntax LEAD(Column_Name, Offset, Default_Value) OVER (ORDER BY Col1, Col2, ...) LAG(Column_Name, Offset, Default_Value) OVER (ORDER BY Col1, Col2, ...) Offset - Number of rows to lead or lag. Default_Value - The default value to return if the number of rows to lead or lag goes beyond first row or last row in a table or partition. If default value is not specified NULL is returned. We will use the following Employees table for the examples in this video SQL Script to create the Employees table Create Table Employees ( Id int primary key, Name nvarchar(50), Gender nvarchar(10), Salary int ) Go Insert Into Employees Values (1, 'Mark', 'Male', 1000) Insert Into Employees Values (2, 'John', 'Male', 2000) Insert Into Employees Values (3, 'Pam', 'Female', 3000) Insert Into Employees Values (4, 'Sara', 'Female', 4000) Insert Into Employees Values (5, 'Todd', 'Male', 5000) Insert Into Employees Values (6, 'Mary', 'Female', 6000) Insert Into Employees Values (7, 'Ben', 'Male', 7000) Insert Into Employees Values (8, 'Jodi', 'Female', 8000) Insert Into Employees Values (9, 'Tom', 'Male', 9000) Insert Into Employees Values (10, 'Ron', 'Male', 9500) Go Lead and Lag functions example WITHOUT partitions : This example Leads 2 rows and Lags 1 row from the current row. When you are on the first row, LEAD(Salary, 2, -1) allows you to move forward 2 rows and retrieve the salary from the 3rd row. When you are on the first row, LAG(Salary, 1, -1) allows us to move backward 1 row. Since there no rows beyond row 1, Lag function in this case returns the default value -1. When you are on the last row, LEAD(Salary, 2, -1) allows you to move forward 2 rows. Since there no rows beyond the last row 1, Lead function in this case returns the default value -1. When you are on the last row, LAG(Salary, 1, -1) allows us to move backward 1 row and retrieve the salary from the previous row. SELECT Name, Gender, Salary, LEAD(Salary, 2, -1) OVER (ORDER BY Salary) AS Lead_2, LAG(Salary, 1, -1) OVER (ORDER BY Salary) AS Lag_1 FROM Employees Lead and Lag functions example WITH partitions : Notice that in this example, Lead and Lag functions return default value if the number of rows to lead or lag goes beyond first row or last row in the partition. SELECT Name, Gender, Salary, LEAD(Salary, 2, -1) OVER (PARTITION By Gender ORDER BY Salary) AS Lead_2, LAG(Salary, 1, -1) OVER (PARTITION By Gender ORDER BY Salary) AS Lag_1 FROM Employees Text version of the video http://csharp-video-tutorials.blogspot.com/2015/10/lead-and-lag-functions-in-sql-server.html Slides http://csharp-video-tutorials.blogspot.com/2015/10/lead-and-lag-functions-in-sql-server_5.html All SQL Server Text Articles http://csharp-video-tutorials.blogspot.com/p/free-sql-server-video-tutorials-for.html All SQL Server Slides http://csharp-video-tutorials.blogspot.com/p/sql-server.html All Dot Net and SQL Server Tutorials in English https://www.youtube.com/user/kudvenkat/playlists?view=1&sort=dd All Dot Net and SQL Server Tutorials in Arabic https://www.youtube.com/c/KudvenkatArabic/playlists
Views: 53523 kudvenkat
SQL: LEAD Function
 
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In this tutorial, you'll learn how to make use of lead function in oracle sql PL/SQL (Procedural Language/Structured Query Language) is Oracle Corporation's procedural extension for SQL and the Oracle relational database. PL/SQL is available in Oracle Database (since version 7), TimesTen in-memory database (since version 11.2.1), and IBM DB2 (since version 9.7).[1] Oracle Corporation usually extends PL/SQL functionality with each successive release of the Oracle Database. PL/SQL includes procedural language elements such as conditions and loops. It allows declaration of constants and variables, procedures and functions, types and variables of those types, and triggers. It can handle exceptions (runtime errors). Arrays are supported involving the use of PL/SQL collections. Implementations from version 8 of Oracle Database onwards have included features associated with object-orientation. One can create PL/SQL units such as procedures, functions, packages, types, and triggers, which are stored in the database for reuse by applications that use any of the Oracle Database programmatic interfaces. PL/SQL works analogously to the embedded procedural languages associated with other relational databases. For example, Sybase ASE and Microsoft SQL Server have Transact-SQL, PostgreSQL has PL/pgSQL (which emulates PL/SQL to an extent), and IBM DB2 includes SQL Procedural Language,[2] which conforms to the ISO SQL’s SQL/PSM standard. The designers of PL/SQL modeled its syntax on that of Ada. Both Ada and PL/SQL have Pascal as a common ancestor, and so PL/SQL also resembles Pascal in several aspects. However, the structure of a PL/SQL package does not resemble the basic Object Pascal program structure as implemented by a Borland Delphi or Free Pascal unit. Programmers can define public and private global data-types, constants and static variables in a PL/SQL package.[3] PL/SQL also allows for the definition of classes and instantiating these as objects in PL/SQL code. This resembles usage in object-oriented programming languages like Object Pascal, C++ and Java. PL/SQL refers to a class as an "Abstract Data Type" (ADT) or "User Defined Type" (UDT), and defines it as an Oracle SQL data-type as opposed to a PL/SQL user-defined type, allowing its use in both the Oracle SQL Engine and the Oracle PL/SQL engine. The constructor and methods of an Abstract Data Type are written in PL/SQL. The resulting Abstract Data Type can operate as an object class in PL/SQL. Such objects can also persist as column values in Oracle database tables. PL/SQL is fundamentally distinct from Transact-SQL, despite superficial similarities. Porting code from one to the other usually involves non-trivial work, not only due to the differences in the feature sets of the two languages,[4] but also due to the very significant differences in the way Oracle and SQL Server deal with concurrency and locking. There are software tools available that claim to facilitate porting including Oracle Translation Scratch Editor,[5] CEITON MSSQL/Oracle Compiler [6] and SwisSQL.[7] The StepSqlite product is a PL/SQL compiler for the popular small database SQLite. PL/SQL Program Unit A PL/SQL program unit is one of the following: PL/SQL anonymous block, procedure, function, package specification, package body, trigger, type specification, type body, library. Program units are the PL/SQL source code that is compiled, developed and ultimately executed on the database. The basic unit of a PL/SQL source program is the block, which groups together related declarations and statements. A PL/SQL block is defined by the keywords DECLARE, BEGIN, EXCEPTION, and END. These keywords divide the block into a declarative part, an executable part, and an exception-handling part. The declaration section is optional and may be used to define and initialize constants and variables. If a variable is not initialized then it defaults to NULL value. The optional exception-handling part is used to handle run time errors. Only the executable part is required. A block can have a label. Package Packages are groups of conceptually linked functions, procedures, variables, PL/SQL table and record TYPE statements, constants, cursors etc. The use of packages promotes re-use of code. Packages are composed of the package specification and an optional package body. The specification is the interface to the application; it declares the types, variables, constants, exceptions, cursors, and subprograms available. The body fully defines cursors and subprograms, and so implements the specification. Two advantages of packages are: Modular approach, encapsulation/hiding of business logic, security, performance improvement, re-usability. They support object-oriented programming features like function overloading and encapsulation. Using package variables one can declare session level (scoped) variables, since variables declared in the package specification have a session scope.
Views: 2228 radhikaravikumar
Oracle Tutorial || Oracle|Adv Sql | Analytical Functions Part-1 by basha
 
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Oracle Partition By clause, Oracle Analytic Functions tutorial
 
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More about analytic functions, visit http://www.learn-with-video-tutorials.com Oracle Analytic Functions and Over By Partition clause enable calculating cumulative and moving aggregates returning multiple rows for each group.
How to Code Oracle Analytic Functions
 
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Many more free Oracle Database and SQL tutorials at http://skillbuilders.com/free-oracle-tutorials. SQL is a language that allows you to perform queries to answer a wide range of questions about your data. While standard SQL is quite powerful, there are many questions that it cannot answer at all or that it can only answer with complex and inefficient SQL workarounds. Questions about running totals, percent of total, and ranking within a group fall into this area. Also, more complex issues such as Top-N within a group and aggregates over a range also fall in this arena. These questions can be easily answered via a new class of SQL statements called Analytic Functions. This presentation will show you how to use Oracle's Analytic Function extensions to SQL to answer these questions simply and efficiently.
Views: 26434 SkillBuilders
Oracle LAG & LEAD Functions / Arabic
 
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--The LAG function is used to access data from a previous row --LAG (value_expression [,offset] [,default]) OVER ([query_partition_clause] order_by_clause) --value_expression - Can be a column or a built-in function, except for other analytic functions. --offset - The number of rows preceeding/following the current row, from which the data is to be retrieved. The default value is 1. --default - The value returned if the offset is outside the scope of the window. The default value is NULL. -- The LEAD function is used to return data from the next row. --LEAD (value_expression [,offset] [,default]) OVER ([query_partition_clause] order_by_clause)
Views: 751 khaled alkhudari
SQL Tutorial - Window Functions - Lag and Lead
 
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Another video brought to you by BeardedDev, bringing you tutorials on Business Intelligence, SQL Programming and Data Analysis. In this video I talk about using Lag and Lead in Windows Functions. This video covers the requirements to pass the exam: If you would like to follow along with the tutorial please run the SQL below: IF OBJECT_ID(N'dbo.Sales', N'U') IS NOT NULL DROP TABLE dbo.Sales; GO CREATE TABLE dbo.Sales ( Sales_Id INT NOT NULL IDENTITY(1, 1) CONSTRAINT PK_Sales_Sales_Id PRIMARY KEY , Sales_Customer_Id INT NOT NULL , Sales_Date DATETIME2 NOT NULL , Sales_Amount DECIMAL (16, 2) NOT NULL ) INSERT INTO dbo.Sales (Sales_Customer_Id, Sales_Date, Sales_Amount) VALUES (1, '20180102', 54.99) , (1, '20180103', 72.99) , (1, '20180104', 34.99) , (1, '20180115', 29.99) , (1, '20180121', 67.00) Lag and Lead are useful for performing trend analysis, in the example I show how we can display a customer spending trend. Lag will show the previous value. Lead will show the next value. Lag and Lead accept multiple parameters as demonstrated in the video: LAG([Column], [Offset], [Value if NULL]) The example of LAG and LEAD in the video can be shown by executing the below SQL query: SELECT Sales_Customer_Id , Sales_Date , LAG(Sales_Amount, 2, 0) OVER(PARTITION BY Sales_Customer_Id ORDER BY Sales_Date) AS PrevValue , Sales_Amount , LEAD(Sales_Amount, 2, 0) OVER(PARTITION BY Sales_Customer_Id ORDER BY Sales_Date) AS NextValue FROM dbo.Sales Please feel free to post comments.
Views: 2593 BeardedDev
Analytic Functions  A Developer’s Best Friend
 
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Timothy Hall, DBA, Developer, Author, Trainer, oracle-base.com Oracle analytic functions are among the most powerful but least understood tools in the Oracle developer’s arsenal. During this presentation, you will be introduced to the analytic function syntax and see demonstrations of some of the most useful analytic functions.
Views: 292 Oracle Developers
ORACLE Analytic Functions for Data Warehousing 1/ Arabic
 
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ORACLE Analytic Functions for Data Warehousing 1/ Arabic --analytic functions allow developers to perform tasks in SQL that were previously confined to procedural languages. -- let's start by aggregate functions ( sum, avg, count,...) select * from EMPLOYEES; select avg(salary) from employees; select DEPARTMENT_ID, avg(salary) from employees group by DEPARTMENT_ID order by 1 /* Analytic functions also operate on subsets of rows, similar to aggregate functions in GROUP BY queries, but they do not reduce the number of rows returned by the query */ select avg(salary) from employees; select employee_id, first_name,salary,(select avg(salary) from employees) avg_sal from EMPLOYEES; --analytic_function([ arguments ]) OVER (analytic_clause) --The analytic_clause breaks down into the following optional elements. --[ query_partition_clause ] [ order_by_clause [ windowing_clause ] ] select employee_id, first_name,salary, avg(salary) over() avg_sal from EMPLOYEES; select employee_id, first_name,salary, avg(salary) over( order by EMPLOYEE_ID ) from EMPLOYEES; select DEPARTMENT_ID, avg(salary) from employees group by DEPARTMENT_ID order by 1 select employee_id, first_name,salary,DEPARTMENT_ID, avg(salary) over(PARTITION BY DEPARTMENT_ID) avg_sal_dept from EMPLOYEES; select employee_id, first_name,salary,DEPARTMENT_ID, avg(salary) over(PARTITION BY DEPARTMENT_ID order by employee_id ) from EMPLOYEES drop table concan_card; create table concan_card ( rec_serial number primary key, game_name varchar2(100), game_round number, player_name varchar2(100), game_round_score number ); insert into concan_card values(1,'GAME1',1,'ahmed', -60); insert into concan_card values(2,'GAME1',1,'khaled', 200); insert into concan_card values(3,'GAME1',1,'ali', 30); insert into concan_card values(4,'GAME1',2,'ahmed', 10); insert into concan_card values(5,'GAME1',2,'khaled', -30); insert into concan_card values(6,'GAME1',2,'ali', 100); insert into concan_card values(7,'GAME1',3,'ahmed', -30); insert into concan_card values(8,'GAME1',3,'khaled', 100); insert into concan_card values(9,'GAME1',3,'ali', 6); select * from concan_card select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY player_name order by player_name,game_round ) from concan_card select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY player_name order by rec_serial ) from concan_card select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY game_name,player_name order by rec_serial ) from concan_card insert into concan_card values(10,'GAME2',1,'ahmed', -60); insert into concan_card values(11,'GAME2',1,'khaled', 200); insert into concan_card values(12,'GAME2',1,'ali', 30); insert into concan_card values(13,'GAME2',2,'ahmed', 10); insert into concan_card values(14,'GAME2',2,'khaled', -30); insert into concan_card values(15,'GAME2',2,'ali', 100); insert into concan_card values(16,'GAME2',3,'ahmed', -30); insert into concan_card values(17,'GAME2',3,'khaled', 100); insert into concan_card values(18,'GAME2',3,'ali', 6); select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY player_name order by player_name,game_round ) from concan_card select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY player_name order by rec_serial ) from concan_card select rec_serial,game_name ,game_round,player_name, game_round_score, sum(game_round_score) over ( PARTITION BY game_name,player_name order by rec_serial ) from concan_card
Views: 5339 khaled alkhudari
Oracle Analytic Function Rank & denseRank
 
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In this video, Rank and Dense_rank function usage is explained with proper example.
Views: 232 amit wadbude
Ask TOM Office Hours: SQL Analytics and Pattern Matching
 
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Held on February 8, 2018 Learn how to make the most of SQL with Chris Saxon, of the AskTOM answer team. Keith Laker joins Chris in this session focusing on problems you can solve using SQL analytic functions. It will also show you can use 12c's pattern matching (match_recognize) to solve these problems in another way. AskTOM Office Hours offers free, monthly training and tips on how to make the most of Oracle Database, from Oracle product managers, developers and evangelists. https://asktom.oracle.com/ Oracle Developers portal: https://developer.oracle.com/ Sign up for an Oracle Cloud trial: https://cloud.oracle.com/en_US/tryit music: bensound.com
Views: 619 Oracle Developers
What the PARTITION BY clause does in Analytic Functions Oracle SQL
 
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In this tutorial video we will learn how to use PARTITION BY clause in Analytic Functions Oracle SQL
Views: 2035 Spod ssppoodd
Analytics: 10 Window clause
 
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blog: https://connor-mcdonald.com Welcome to the KISS video series. Solving problems that typically required complicated SQL in the past, that can now be easily solved with Analytic SQL syntax. In this session, we take our first look at the final clause in our analytic syntax - the WINDOW clause The sample problem we'll solve is: How analytic aggregation returns two types of aggregates - either reporting or windowing aggregates. Scripts: https://livesql.oracle.com/apex/livesql/file/content_CQXSUXL3JBUOBC82NO9SKKGLE.html
Views: 672 Connor McDonald
SQL Query Training   70 461 TOP Ranking and Analytic functions
 
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Additional Training: http://amzn.to/1RjjJCf Other Trainings: www.AaronBuma.com/free-sql-server-training/ We cover features around the TOP(N) in your query, followed by using the RANK(), DENSE_RANK and ROW_NUMBER. Then on to Analytic Functions to help with your statistical analysis of data. Similar to aggregate functions, analytics functions compute over a group of rows with multiple results within each group. Learn how to properly use each of these analytics functions in combination with enhancements to the OVER clause. Learn the value of CUME_DIST and PERCENT_RANK in your analysis, use LAST_VALUE and FIRST_VALUE along with PERCENTILE_DISC, PERCENTILE_CONT, LEAD and LAG you can look at data in the next and previous row. For previous presentations and notifications of upcoming events, checkout my blog: www.AaronBuma.com or follow @AaronDBuma Slides and scripts are also available at: www.AaronBuma.com
Views: 10010 Aaron Buma
Analytics: 17 The LAG / LEAD clauses
 
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blog: https://connor-mcdonald.com Welcome to the KISS video series. Solving problems that typically required complicated SQL in the past, that can now be easily solved with Analytic SQL syntax. In this session, we look at the lag and lead functions. The sample problem we'll solve is: Collapsing repeated rows in an order history table to show only the days where the order changed status Scripts: https://livesql.oracle.com/apex/livesql/file/content_CZUCT0MCOQZMJM7TI553HC8S9.html
Views: 481 Connor McDonald
What is LAG Function in Oracle
 
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What is LAG Function in Oracle How to Get Previous Record in SQL How to Get Previous Salary in Oracle SQL Tutorial SQL Tutorial for beginners PLSQL Tutorial PLSQL Tutorial for beginners PL/SQL Tutorial PL SQL Tutorial PL SQL Tutorial for beginners PL/SQL Tutorial for beginners Oracle SQL Tutorial
Views: 399 TechLake
Oracle DENSE_RANK Function
 
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https://www.databasestar.com/oracle-dense_rank/ The Oracle DENSE_RANK function allows you to calculate a rank of a row in a group of rows. It returns this rank as a NUMBER value. This function can be used as either an analytic or an aggregate function, and the syntax depends on how you use it. As an aggregate function it looks like this: DENSE_RANK ( expr, [expr(n)] ) WITHIN GROUP ( ORDER BY (order_expr [ASC|DESC] [NULLS FIRST|LAST] ) These parameters are: - expr: this is the value to search for in a particular table. You can specify multiple search values, and just separate them by a comma. - order_expr: this is used to order the expr values by, because you get a different results depending on what order you rank the values in. - NULLS FIRST or LAST: this is where you can specify if you want to have NULL values appear at the top of your ranking order or at the bottom. As an analytic function, it looks like this: DENSE_RANK() OVER ( [query_partition_clause] order_by_clause) The parameters are: - query_partition_clause: this is the expression that the ranking is “grouped” by, as analytic functions allow you to group data within rows. - order_by_clause: this is the expression to order your results by to determine a rank. For this function, if two records have the same sort or rank position, they will have the same RANK value. It won’t cause a gap in the rankings, unlike the RANK function which does cause a gap. For more information about the Oracle DENSE_RANK function, including all of the SQL shown in this video and the examples, read the related article here: https://www.databasestar.com/oracle-dense_rank/
Views: 483 Database Star
LEAD Analytical function in PL SQL.
 
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How to get nth highest record using Lead Analytical function in PL SQL. Use of Analytical Functions in Oracle pl sql makes it easy to find the nth leading value with respect to your current record. Watch this pl sql tutorial and you can understant the use of lead function in sql.
Views: 630 Subhroneel Ganguly
NTILE() Analytical Function in Oracle Database
 
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NTILE Function in Oracle
Views: 67 Adam Tech
Windowing Functions in Spark SQL Part 1 | Lead and Lag Functions | Windowing Functions Tutorial
 
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Windowing Functions in Spark SQL Part 1 | Lead and Lag Functions | Windowing Functions Tutorial https://acadgild.com/big-data/big-data-development-training-certification?utm_source=youtube&utm_medium=organic&utm_campaign=Yotube_MViPRjaqfaA-window-function-spark-1_20180507 Hello and welcome back to Hadoop tutorials powered by Acadgild. In this tutorial, you will be able to learn the windowing functions in Spark SQL. Let’s start understanding the internals of lag and lead functions in this lecture. These are some inbuilt functions which operate on a set of rows and return a single value for each row from the underlying query. This can be very useful to simplify complex queries and break them down into logical components. To give you a brief idea about these windowing functions in spark, we will be using stock market data. Dataset Link: https://drive.google.com/open?id=1nWGndnKxCNi5WKqPMBbrEhp4CBIWb7O- Commands Download link: https://drive.google.com/open?id=145J2F07thkx17FeogVxiw6fctsDlhDrb Let's now understand the input(Dataset) and expected the output of the lag function. Show the document consisting of sample input and output and explain it 1st column in this dataset is the date, 2nd column is the ticker which is nothing but the stock name, 3rd column is the open value of a stock, 4th column is the closing value of the stock, and the last column is the volume of the stocks on that particular day. in the sample output, we perform the query to retrieve ticker, date, closing price of a stock on a particular day and the derived column is the closing value of the same stock on the previous day Watch the complete video followed by execution of the same. Please subscribe and stay tuned for more such videos. #sparksql, #windowing, #Hadoop, #bigdata For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 2274 ACADGILD
ORACLE Analytic Functions for Data Warehousing 2/ Arabic
 
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ORACLE Analytic Functions for Data Warehousing 2/ Arabic FIRST_VALUE last_VALUE row_number() --FIRST_VALUE and LAST_VALUE Analytic Functions select EMPLOYEE_ID, FIRST_NAME, HIRE_DATE from employees order by hire_date; select EMPLOYEE_ID, FIRST_NAME, HIRE_DATE , min(HIRE_DATE) over ( ) first_HIRE_DATE from employees select EMPLOYEE_ID, FIRST_NAME, HIRE_DATE , FIRST_VALUE(HIRE_DATE) over ( ) first_HIRE_DATE from employees order by hire_date; select EMPLOYEE_ID, FIRST_NAME, HIRE_DATE , max(HIRE_DATE ) over ( ) last_HIRE_DATE from employees select EMPLOYEE_ID, FIRST_NAME, HIRE_DATE , last_VALUE(HIRE_DATE ) over ( ) last_HIRE_DATE from employees order by HIRE_DATE drop table student_exam_result; CREATE TABLE student_exam_result (student_id number, exame_name varchar2(100), exame_try number, exame_results number ); insert into student_exam_result values(1,'calcluas',1,50); insert into student_exam_result values(1,'calcluas',2,66); insert into student_exam_result values(1,'calcluas',3,20); insert into student_exam_result values(2,'calcluas',1,66); insert into student_exam_result values(2,'calcluas',2,null); insert into student_exam_result values(2,'calcluas',3,7); insert into student_exam_result values(3,'calcluas',1,50); insert into student_exam_result values(3,'calcluas',2,98); insert into student_exam_result values(3,'calcluas',3,null); select * from student_exam_result select student_id, exame_name,exame_try,exame_results, last_value(exame_results) IGNORE NULLS over (PARTITION BY student_id, exame_name ) last_grade from student_exam_result order by student_id, exame_name, exame_try select student_id, exame_name,exame_try,exame_results, last_value(exame_results) IGNORE NULLS over (PARTITION BY student_id, exame_name ) last_grade, max(exame_results) over (PARTITION BY student_id, exame_name ) max_grade, avg(exame_results) over (PARTITION BY student_id, exame_name ) avg_grade from student_exam_result order by student_id, exame_name, exame_try ------------------------ select employee_id,first_name ,row_number() over(order by employee_id ) from employees select employee_id,first_name ,rownum from employees select employee_id,first_name ,department_id, row_number() over(partition by department_id order by employee_id ) from employees
Views: 753 khaled alkhudari
Window functions in SQL Server
 
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sql server window function example window function sql server example sql server rows range clause sql server rows between 1 preceding and 1 following In this video we will discuss window functions in SQL Server In SQL Server we have different categories of window functions Aggregate functions - AVG, SUM, COUNT, MIN, MAX etc.. Ranking functions - RANK, DENSE_RANK, ROW_NUMBER etc.. Analytic functions - LEAD, LAG, FIRST_VALUE, LAST_VALUE etc... OVER Clause defines the partitioning and ordering of a rows (i.e a window) for the above functions to operate on. Hence these functions are called window functions. The OVER clause accepts the following three arguments to define a window for these functions to operate on. ORDER BY : Defines the logical order of the rows PARTITION BY : Divides the query result set into partitions. The window function is applied to each partition separately. ROWSor RANGE clause : Further limits the rows within the partition by specifying start and end points within the partition. The default for ROWS or RANGE clause is RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW Let us understand the use of ROWS or RANGE clause with an example. Compute average salary and display it against every employee We might think the following query would do the job. SELECT Name, Gender, Salary, AVG(Salary) OVER(ORDER BY Salary) AS Average FROM Employees As you can see from the result, the above query does not produce the overall salary average. It produces the average of the current row and the rows preceeding the current row. This is because, the default value of ROWS or RANGE clause (RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) is applied. To fix this, provide an explicit value for ROWS or RANGE clause as shown below. ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING tells the window function to operate on the set of rows starting from the first row in the partition to the last row in the partition. SELECT Name, Gender, Salary, AVG(Salary) OVER(ORDER BY Salary ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING) AS Average FROM Employees The same result can also be achieved by using RANGE BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING Well, what is the difference between ROWS and RANGE We will discuss this in a later video The following query can be used if you want to compute the average salary of 1. The current row 2. One row PRECEDING the current row and 3. One row FOLLOWING the current row SELECT Name, Gender, Salary, AVG(Salary) OVER(ORDER BY Salary ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING) AS Average FROM Employees Text version of the video http://csharp-video-tutorials.blogspot.com/2015/10/window-functions-in-sql-server.html Slides http://csharp-video-tutorials.blogspot.com/2015/10/window-functions-in-sql-server_7.html All SQL Server Text Articles http://csharp-video-tutorials.blogspot.com/p/free-sql-server-video-tutorials-for.html All SQL Server Slides http://csharp-video-tutorials.blogspot.com/p/sql-server.html All Dot Net and SQL Server Tutorials in English https://www.youtube.com/user/kudvenkat/playlists?view=1&sort=dd All Dot Net and SQL Server Tutorials in Arabic https://www.youtube.com/c/KudvenkatArabic/playlists
Views: 63752 kudvenkat
Analytical functions in oracle part 1
 
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Rank ,Dense Rank and Row number function in oracle
Views: 240 DataSmith
Oracle Tutorials | Analytical Functions in Oracle | by Mr.Sudhakar L
 
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Oracle Tutorials | Analytical Functions in Oracle | by Mr.Sudhakar L Introduction to Analytic Functions Introduction to Analytic Functions in Oracle ** For Online Training Registration: https://goo.gl/r6kJbB ► Call: +91-8179191999 ► Visit Our Website for Classroom Training: https://nareshit.in ► For Online Training: https://nareshit.com/ -------------------------- ► About NareshIT: "Naresh IT is having 14+ years of experience in software training industry and the best Software Training Institute for online training, classroom training, weekend training, corporate training of Hadoop, Salesforce, AWS, DevOps, Spark, Data Science, Python, Tableau, RPA ,Java, C#.NET, ASP.NET, Oracle, Testing Tools, Silver light, Linq, SQL Server, Selenium, Android, iPhone, C Language, C++, PHP and Digital Marketing in USA,Hyderabad, Chennai and Vijayawada,Bangalore India which provides online training across all the locations -------------------------- ► Our Online Training Features: 1.Training with Real-Time Experts 2.Industry Specific Scenario’s 3.Flexible Timings 4.Soft Copy of Material 5. Share Videos of each and every session. -------------------------- Please write back to us at [email protected]/[email protected] or Call us at USA: +1404-232-9879 or India: +918179191999 ** Check The Below Links** ► For Course Reg: https://goo.gl/r6kJbB ► Subscribe to Our Channel: https://goo.gl/q9ozyG ► Circle us on G+: https://plus.google.com/NareshIT ► Like us on Facebook: https://www.facebook.com/NareshIT ► Follow us on Twitter: https://twitter.com/nareshitech ► Follow us on Linkedin: https://in.linkedin.com/company/naresh-i-technologies ► Follow us on Instagram: https://www.instagram.com/nareshitech/
Views: 2180 Naresh i Technologies
Oracle Pl/Sql Analytical Function Example
 
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Oracle Pl/Sql Analytical Function Example
Views: 1000 Subhroneel Ganguly
Oracle Analytic Functions In-Depth / NEW UDEMY COURSE
 
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To all my students that enrolled in my Oracle SQL & PL/SQL course: It is time now for advanced SQL, the Best Course Ever and the only course in udemy which talk about this topic in details You will learn many things: • Use SQL with aggregation operators. • SQL for Analysis and Reporting functions • Group and aggregate data using the ROLLUP and CUBE operators • The GROUPING function • Composite Columns and the concatenated Groupings • RANK & DENSE_RANK • PERCENT_RANK • CUME_DIST (cumulative distribution) • The LAG/LEAD Functions • LISTAGG function • Aggregate functions VS Analytic Part • Aggregate functions & windowing clause In-Depth • Moving Average and running totals • ROWNUM & ROW_NUMBER • And much more Take it now 10.99$ https://www.udemy.com/oracle-analytic-functions-in-depth/?couponCode=KHKH10
Views: 703 khaled alkhudari
Analytical Functions | ORACLE/ SQL
 
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Analytical Functions are used in ORACLE/SQL ..... RANK,DENSE_RANK, LEAD,LAG,AND LISTTAG ARE ANALYTICAL FUNCTIONS
Views: 9309 Adam Tech
SQL: Analytical Functions
 
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In this tutorial, you'll learn how to use the analytical functions..
Views: 37909 radhikaravikumar
SQL Tutorial for beginners What is LEAD Function in Oracle
 
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What is LEAD Function in Oracle SQL Tutorial SQL Tutorial for beginners PLSQL Tutorial PLSQL Tutorial for beginners PL/SQL Tutorial PL SQL Tutorial PL SQL Tutorial for beginners PL/SQL Tutorial for beginners Oracle SQL Tutorial
Views: 264 TechLake
KISS series on Analytics: 17 The LAG / LEAD clauses
 
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Welcome to the KISS video series. Solving problems that typically required complicated SQL in the past, that can now be easily solved with Analytic SQL syntax. In this session, we look at the lag and lead functions. The sample problem we'll solve is: Collapsing repeated rows in an order history table to show only the days where the order changed status Scripts: https://livesql.oracle.com/apex/livesql/file/content_CZUCT0MCOQZMJM7TI553HC8S9.html Watch the entire Analytics playlist at https://www.youtube.com/playlist?list=PLJMaoEWvHwFJDyhMLCkNSSUQWw9waFkIj ========================================­­­============== Copyright © 2015 Oracle and/or its affiliates. Oracle is a registered trademark of Oracle and/or its affiliates. All rights reserved. Other names may be registered trademarks of their respective owners. Oracle disclaims any warranties or representations as to the accuracy or completeness of this recording, demonstration, and/or written materials (the “Materials”). The Materials are provided “as is” without any warranty of any kind, either express or implied, including without limitation warranties or merchantability, fitness for a particular purpose, and non-infringement.
Views: 1010 Connor McDonald
FIRST_VALUE and LAST_VALUE Analytic Functions in Oracle Database
 
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FIRST_VALUE and LAST_VALUE in Oracle Database Oracle FIRST Function Oracle last Function
Views: 126 Adam Tech
SQL Tutorial - Window Functions
 
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For the best book on T-SQL click here: https://www.amazon.co.uk/gp/product/0735685045/ref=as_li_tl?ie=UTF8&camp=1634&creative=6738&creativeASIN=0735685045&linkCode=as2&tag=beardeddev-21&linkId=2e450454659d4279f54dd188d24bc011 Another fantastic SQL Tutorial brought to you by BeardedDev. In this video we begin to explore Window Functions and their purpose within SQL Server. Window Functions are used for performing data analysis calculations and address an important need compared to the GROUP BY clause that we are able to return the underlying data in the same query. This video shows an example of the differences between the GROUP BY clause and Window Functions. Window Functions were first introduced in SQL Server 2005 but further enhancements and support was added in SQL Server 2012. We look at the OVER clause and PARTITION BY. Window Functions can only be included within SELECT or ORDER BY clauses. Functions Available: Aggregate - COUNT, SUM, MIN, MAX, AVG Offset - FIRST_VALUE, LAST_VALUE, LEAD, LAG Statistical - PERCENT_RANK, CUME_DIST, PERCENTILE_CONT, PERCENTILE_DIST Windows Functions also have FRAMES ROWS RANGE Window Functions are a powerful tool within SQL Server and I am excited to bring more videos and tutorials working with Window Functions in the future. Code: WITH CTE AS ( SELECT Sales_Id , SUM(Line_Total) AS Total FROM Sales_Details GROUP BY Sales_Id ) SELECT * FROM CTE AS A INNER JOIN Sales_Details AS B ON A.Sales_Id = B.Sales_Id SELECT Sales_Id , Sales_Date , Item , Price , Quantity , Line_Total , COUNT(Line_Total) OVER(PARTITION BY Sales_Id) AS Line_Count , SUM(Line_Total) OVER(PARTITION BY Sales_Id) AS Sales_Total , SUM(Line_Total) OVER(PARTITION BY Sales_Date) AS Daily_Total , SUM(Line_Total) OVER() AS Total FROM Sales_Details ORDER BY Sales_Total
Views: 13322 BeardedDev
Syntax of Analytic Functions in Oracle SQL
 
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In this tutorial video tutorial we will learn Syntax of Oracle SQL Analytic Functions
Views: 75 Spod ssppoodd
Oracle LISTAGG Function
 
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https://www.databasestar.com/oracle-listagg/ The Oracle LISTAGG function allows you to aggregate or combine string values from multiple rows into a single row. For example, it turns this data: FIRST_NAME Adam Brad Carrie Into this data: FIRST_NAME Adam, Brad, Carrie The same data is shown, but it’s in one row and not multiple. It’s a valuable string manipulation function, and once you know what it is and how it works, you’ll be able to use it in your queries as needed. So what does it look like? The function is: LISTAGG ( measure_expr [, delimiter]) WITHIN GROUP (order_by_clause) [OVER query_partition_clause] These parameters are: measure_expr: This is a column or expression that you want to concatenate the values of. In the example above, it was the first_name column. Mandatory. delimiter: This is the character between each of the measure_expr values. Optional, the default is a comma. order_by_clause: This is the order that the values from the measure_expr are listed. Mandatory. query_partition_clause: This allows you to use LISTAGG as an analytic function, allowing you to show LISTAGG in groups for different rows. One thing to be aware of is that the output of the Oracle LISTAGG function is limited to 4,000 bytes. If you get more than this, you’ll receive an error. The most common way around this that I’ve seen is to write a custom function and use a CLOB. Watch the video to find out more and see some examples. For more information about the Oracle LISTAGG function, including all of the SQL shown in this video and the examples, read the related article here: https://www.databasestar.com/oracle-listagg/
Views: 3190 Database Star
LAG vs LEAD Functions in Oracle Database
 
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LEAD Function in Oracle Database LAG Function in Oracle Database
Views: 31 Adam Tech
IBM Netezza Basic Analytical Functions
 
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This video talks about below analytical functions: 1)RANK 2) DENSE_RANK 3) ROW_NUMBER 4) LAG 5) LEAD and the difference between aggregate and analytical functions.
Views: 1842 Etraining Guru
LAG analytical function in plsql.
 
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How to use LAG analytical function in plsql to find the nth nearest record from the top.Watch this pl sql tutorial on lag analytical functions in oracle to find out records with nth lagging values.
Views: 505 Subhroneel Ganguly
Alex Nuijten - Analytic Functions: Unleash the SQL Power
 
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Analytic Functions have been around for quite a long time, and still they are a relatively unknown. If you are unfamiliar with these very powerful functions, you are missing out on something spectacular. Analytic Functions add inter-row calculations, aggregates over multiple dimensions, or rank assignment based on values within a group of values - all without a GROUP BY clause. The syntax might seem daunting at first, but it is really not that scary. This session will focus on the syntax with tons of real world uses for Analytic Functions.
Views: 963 Riga Dev Days
Oracle Analytic Functions
 
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In this video I have covered the Oracle Analytic Functions. Analytic Function: Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a window and is defined by the analytic_clause.
Views: 68 Ajeet Verma
LEAD, LAG in SQL Server
 
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Click here to Subscribe to IT PORT Channel : https://www.youtube.com/channel/UCMjmoppveJ3mwspLKXYbVlg From SQL Server 2012, this feature enhanced to OVER Windowing Functions Accesses data from a subsequent row in the same result set without the use of a self-join. LEAD provides access to a row at a given physical offset that follows the current row. LAG provides access to a row at a given physical offset that before the current row. Using this analytic function in a SELECT statement, We can compare value of current row with Previous Or Following Rows.
Views: 379 IT Port
What Oracle SQL analytic functions are?
 
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In this training video we will learn how to usу analytic SQL functions in Oracle
Views: 60 Spod ssppoodd

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