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Oracle Hints Tutorial for improving performance
 
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Oracle Hints Tutorial for improving performance APPEND PARALLEL JOIN INDEX NO_INDEX SELECT /*+ FIRST_ROWS(10) */ * FROM emp WHERE deptno = 10; SELECT /*+ ALL_ROWS */ * FROM emp WHERE deptno = 10; SELECT /*+ NO_INDEX(emp emp_dept_idx) */ * FROM emp, dept WHERE emp.deptno = dept.deptno; SELECT /*+ INDEX(e,emp_dept_idx) */ * FROM emp e WHERE e.deptno = 10; -- SELECT /*+ INDEX(scott.emp,emp_dept_idx) */ * FROM scott.emp; SELECT /*+ AND_EQUAL(e,emp_dept_idx) */ * FROM emp e; SELECT /*+ INDEX_JOIN(e,emp_dept_idx) */ * FROM emp e; SELECT /*+ PARALLEL_INDEX(e,emp_dept_idx , 8) */ * FROM emp e; SELECT /*+ LEADING (dept) */ * FROM emp, dept WHERE emp.deptno = dept.deptno; SELECT /*+ PARALLEL(8) CACHE (e) FULL (e) */ * FROM emp e ; SELECT /*+ PARALLEL FULL (e) */ * FROM emp e ; SELECT /*+ PARALLEL USE_MERGE (emp dept) */ * FROM emp, dept WHERE emp.deptno = dept.deptno; -- SORT Merge Join SELECT /*+ PARALLEL USE_HASH (emp dept) */ * FROM emp, dept WHERE emp.deptno = dept.deptno; -- Hash Join SELECT /*+ PARALLEL */ * FROM emp e ; INSERT /*+ APPEND */ INTO mytmp select /*+ CACHE (e) */ *from emp e; commit;
Views: 8486 TechLake
DBMS Indexing: The Basic Concept
 
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A quick introduction to the concept of indexing in RDBMSs
Views: 168442 Brian Finnegan
PART 5.4 Types of Indexing in DBMS in HINDI different classification of indexing physical secondary
 
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Thank you friends for watching the video. Please Like the video if it has helped you in any way & do subscribe to the channel. This video discuss the Types of Indexing in database in hindi. Important topic of database Indexing like need of indexing in database management indexing, Why we do indexing in files in database, How we do indexing in dbms, Types of indexing, Methods of Indexing, Advantages of Indexing,How to access a file fast in database, Single level Indexing in database file, Multilevel indexing in database file structure in dbms,Primary Indexing in database, Clustered Indexing in database,Secondary Indexing file in dbms, Advantages of using single level Indexing in database are discussed. Single level index: This means we create index file for the main file, and then stop the process. Multiple level index:This means, we further index the index file and keep repeating the process until we get one block.Multi-level Index helps in breaking down the index into several smaller indices in order to make the outermost level so small that it can be saved in a single disk block-0, which can easily be accommodated anywhere in the main memory. A.) PRIMARY INDEXING- i) Main file is always sorted according to primary key. ii) Indexing is done on Primary Key, therefor called as primary indexing B.) CLUSTERED INDEXING: - i) Main file will be ordered on some non-key attributes ii) No of entries in the index file = no of unique values of the attribute on which indexing is done. iii) It is the example of Sparse as well as dense indexing C.) SECONDARY INDEXING- i) Most common scenarios, Suppose that we already have a primary indexing on primary key, but there are frequent query on some other attributes , so we may decide to have one more index file with some other attribute. ii) Main file is ordered according to the attribute on which indexing is done(unordered). iii) Secondary indexing can be done on key or non-key attribute. iii) It is an example of dense indexing. Please spare some time and fill this form so that we can know about you and what you think about us: https://goo.gl/forms/b5ffxRyEAsaoUatx2 Your review/recommendation and some words can help validating our quality of content and work.. so Please do the following: - 1) Give us a 5 star review with comment on Google https://goo.gl/maps/sLgzMX5oUZ82 2) Follow our Facebook page and give us a 5 star review with comments https://www.facebook.com/pg/knowledgegate.in/reviews 3) Follow us on Instagram https://www.instagram.com/mail.knowledgegate/ DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,Partial Dependency, Multivalued dependency,Indexing,Hashing, B tree,B+ tree,Ordered Indexing,Select operation,Join operations, Natural joins, SQL commands,File structure in DBMS,Primary Indexing,Clustered Indexing,Concurrency control protocols, Transaction Management in DBMS,ACID properties, Data Consistency, Concurrency in database,Deadlock in database, Deadlock handling, Database Recovery, Deadlock avoidance, Deadlock prevention,Scheduling in dbms, Conflict Serializability, Serial Schedules, Two phase locking,SQL commands,DBMS for gate , DBMS for net, DBMS lectures, DBMS tutorials, DBMS for beginners, learn DBMS, Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Primary Indexing in DBMS, Secondary Indexing in database management system, Clustered indexing in database, indexing in dbms tutorial hindi, Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Primary Indexing in DBMS, Secondary Indexing in database management system, Clustered indexing in database, indexing in dbms tutorial hindi,
Views: 107797 KNOWLEDGE GATE
SQL tutorial 62: Indexes In Oracle Database By Manish Sharma RebellionRider
 
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Watch and learn concepts of SQL Index In Oracle Database. In this tutorial you will learn about B-Tree Index and Function based Index. ------------------------------------------------------------------------ ►►►LINKS◄◄◄ Blog : Previous Tutorial ► ------------------------------------------------------------------------- ►►►Help Me In Getting A Job◄◄◄ ►Help Me In Getting A Good Job By Connecting With Me on My LinkedIn and Endorsing My Skills. All My Contact Info is Down Below. You Can Also Refer Me To Your Company Thanks ------------------------------------------------------------------------- Copy Cloud referral link || Use this link to join copy cloud and get 20GB of free storage https://copy.com?r=kb4rc1 -------------------------------------------------------------------------- ►Make sure you SUBSCRIBE and be the 1st one to see my videos! -------------------------------------------------------------------------- Amazon Wishlist: http://bit.ly/wishlist-amazon ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ►►►Find me on Social Media◄◄◄ Follow What I am up to as it happens on https://twitter.com/rebellionrider https://www.facebook.com/imthebhardwaj http://instagram.com/rebellionrider https://plus.google.com/+Rebellionrider http://in.linkedin.com/in/mannbhardwaj/ http://rebellionrider.tumblr.com/ http://www.pinterest.com/rebellionrider/ You can also Email me at for E-mail address please check About section Please please LIKE and SHARE my videos it makes me happy. Thanks for liking, commenting, sharing and watching more of our videos This is Manish from RebellionRider.com ♥ I LOVE ALL MY VIEWERS AND SUBSCRIBERS
Views: 42274 Manish Sharma
PART 5.3 Indexing in dbms in hindi basics of indexing in dbms primary secondary clustered
 
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Thank you friends for watching the video. Please Like the video if it has helped you in any way & do subscribe to the channel. This video discuss the concept of Indexing in database in hindi. Important topic of database Indexing like need of indexing in database management indexing, Why we do indexing in files in database, How we do indexing in dbms, Types of indexing, Methods of Indexing, Advantages of Indexing,How to access a file fast in database, Single level Indexing in database file, Multilevel indexing in database file structure in dbms,Dense indexing in database, Sparse Indexing in database,Index file in dbms, Advantages of using Index file in database are discussed. What is Indexing: Additional auxiliary access structure are called indexes, a data technique to efficiently retrieve records from the database files based on some attributes on which the indexing has been done. Dense Index: 1) In dense index, there is an entry in the index file for every search key value in the main file. This makes searching faster but requires more space to store index records itself. 2) Note that it is not for every record, it is for every search key value. Some time number of records in the main file is greater than equal to number of search keys in the main file, for example if search key is repeated. Sparse Index: 1) If an index entry is created only for some records of the main file, then it is called sparse index. 2) No. of index entries in the index file → No. of records in the main file. Please spare some time and fill this form so that we can know about you and what you think about us: https://goo.gl/forms/b5ffxRyEAsaoUatx2 Your review/recommendation and some words can help validating our quality of content and work.. so Please do the following: - 1) Give us a 5 star review with comment on Google https://goo.gl/maps/sLgzMX5oUZ82 2) Follow our Facebook page and give us a 5 star review with comments https://www.facebook.com/pg/knowledgegate.in/reviews 3) Follow us on Instagram https://www.instagram.com/mail.knowledgegate/ DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,Partial Dependency, Multivalued dependency,Indexing,Hashing, B tree,B+ tree,Ordered Indexing,Select operation,Join operations, Natural joins, SQL commands,File structure in DBMS,Primary Indexing,Clustered Indexing,Concurrency control protocols, Transaction Management in DBMS,ACID properties, Data Consistency, Concurrency in database,Deadlock in database, Deadlock handling, Database Recovery, Deadlock avoidance, Deadlock prevention,Scheduling in dbms, Conflict Serializability, Serial Schedules, Two phase locking,SQL commands,DBMS for gate , DBMS for net, DBMS lectures, DBMS tutorials, DBMS for beginners, learn DBMS, Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization,
Views: 167732 KNOWLEDGE GATE
Oracle 11g Hints Overview
 
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In this Video tutorial we will discuss about Optimizer hints in Oracle. What is optimizer hint, when & why its needed. Different Category of hints. Description of mostly used hints. Demonstrate how query plan can change with the influence of hint.
Views: 53200 Anindya Das
PART 5.7 Clustering Index | DBMS HINDI |
 
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Thank you friends for watching the video. Please Like the video if it has helped you in any way & do subscribe to the channel. This video contains the detailed discussion of clustered indexing in dbms with example. Detail explanation of Clustered Indexing, Example of Clustered Indexing, How Clustered indexing works in dbms,Need of Clustered Indexing, Where Clustered Indexing is used,Advantages of Clustered Indexing,Properties of Clustered Indexing in dbms, Properties of single level indexing, Questions of Clustered Indexing,Numericals on Clustered Indexing for gate exam, How Clustered indexing works on file is explained. CLUSTERED INDEXING: - i)Main file will be ordered on some non-key attributes ii)No of entries in the index file = no of unique values of the attribute on which indexing is done. iii)It is the example of Sparse as well as dense indexing Block access required will be greater than equal to log2n +1, where n is no of block acquired by Index file. Please spare some time and fill this form so that we can know about you and what you think about us: https://goo.gl/forms/b5ffxRyEAsaoUatx2 Your review/recommendation and some words can help validating our quality of content and work.. so Please do the following: - 1) Give us a 5 star review with comment on Google https://goo.gl/maps/sLgzMX5oUZ82 2) Follow our Facebook page and give us a 5 star review with comments https://www.facebook.com/pg/knowledgegate.in/reviews 3) Follow us on Instagram https://www.instagram.com/mail.knowledgegate/ DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,Partial Dependency, Multivalued dependency,Indexing,Hashing, B tree,B+ tree,Ordered Indexing,Select operation,Join operations, Natural joins, SQL commands,File structure in DBMS,Primary Indexing,Clustered Indexing,Concurrency control protocols, Transaction Management in DBMS,ACID properties, Data Consistency, Concurrency in database,Deadlock in database, Deadlock handling, Database Recovery, Deadlock avoidance, Deadlock prevention,Scheduling in dbms, Conflict Serializability, Serial Schedules, Two phase locking,SQL commands,DBMS for gate , DBMS for net, DBMS lectures, DBMS tutorials, DBMS for beginners, learn DBMS, Clustered Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in Clustered indexing in database,Clustered indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Clustered Indexing in DBMS,numerical of Clustered indexing in dbms, solved question of Clustered indexing in dbms,indexing in dbms tutorial for Gate, Net hindi, Clustered Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in Clustered indexing in database,Clustered indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Clustered Indexing in DBMS,numerical of Clustered indexing in dbms, solved question of Clustered indexing in dbms,indexing in dbms tutorial for Gate, Net hindi, DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,
Views: 77703 KNOWLEDGE GATE
Indexing in dbms | dbms indexing in hindi | Introduction to Indexing | DBMS Lectures in Hindi #85
 
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Welcome to series of gate lectures by well academy GATE Practice Book Purchase Link ( ACE Academy ) https://goo.gl/jESdtD GATE Practice Book Purchase Link ( Made Easy ) https://goo.gl/zUU5Vn Here are some more GATE lectures by well academy SQL create table in hindi | SQL tutorial in hindi | DBMS Lectures in hindi #72 : https://youtu.be/Pm8XAQYDBGw constraints in dbms | constraints in sql in hindi | DBMS Lectures in Hindi #73 : https://youtu.be/kevkLGrJvUg sql insert command | sql insert into table | sql insert query | DBMS Lectures in hindi #74 : https://youtu.be/lsxyUFjh148 SQL Delete row | SQL Update Query | sql queries tutorial in hindi | DBMS Lectures in hindi #75 : https://youtu.be/KuUPDpYKtT0 referential integrity constraint in dbms | referential integrity in sql | DBMS Lectures in Hindi #76 : https://youtu.be/UT_8T7EL2Og SQL Alter command | sql alter table add column | dbms queries tutorial | DBMS Lectures in Hindi #77 : https://youtu.be/uCjKTMdy094 sql select query | sql select statement | sql select from multiple tables | dbms Lectures #78 : https://youtu.be/-Lo6KHlkiQk create view in sql | view in sql in hindi | View Operation in SQL | DBMS Lectures in Hindi #79 : https://youtu.be/YURtgFm0cIk SQL Pattern Matching | LIKE Condition | DBMS Gate Lectures in hindi #80 : https://youtu.be/goMsplCB730 arithmetic operators in SQL | SQL Arithmatic Operators | DBMS Lectures in Hindi #81 : https://youtu.be/kAfHeYfTXFI SQL order by | sql order by tutorial | dbms queries tutorial | DBMS Lectures in Hindi #82 : https://youtu.be/E8p1HzzCUW0 file organization in dbms | file organization in database | file organization in dbms in hindi #83 : https://youtu.be/ofslaTIpT8A organization of records in files in dbms | Ordered and Unordered | DBMS Lectures in hindi #84 : https://youtu.be/AsrQuq53xRI Facebook Me : https://goo.gl/2zQDpD Click here to subscribe well Academy https://www.youtube.com/wellacademy1 GATE Lectures by Well Academy Facebook Group https://www.facebook.com/groups/1392049960910003/ Thank you for watching share with your friends Follow on : Facebook page : https://www.facebook.com/wellacademy/ Instagram page : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy file indexing in dbms, indexing in dbms in hindi, indexing in dbms with examples, types of indexing in dbms, dbms indexing gate, dbms indexing, dbms indexing gate, dbms indexing in hindi, indexing in dbms in hindi, indexing structures in dbms, indexing in dbms, indexing in dbms for gate, indexing in dbms in english, multilevel indexing in dbms,
Views: 15716 Well Academy
(SQL튜닝)오라클 힌트 강좌#8  인덱스 영역에서 데이터를  스캐닝 하기 위한 힌트 (INDEX, INDEX_ASC, INDEX_DESC힌트)
 
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오라클 힌트 강좌#8 인덱스 영역에서 데이터를 스캐닝 하기 위한 힌트 (INDEX, INDEX_ASC, INDEX_DESC힌트) Hints For Access Paths(INDEX_ASC)  INDEX 힌트와 동일한데 인덱스가 생성된 형태대로 인덱스를 스캔 하라는 의미의 힌트이다. 이 힌트를 이용하여 데이터를 추출하게 되면 화면에 나타나는 데이터는 인덱스를 생성한 순서대로 데이터가 추출된다.  인덱스 영역에서 인덱스가 생성된 형태 대로 순방향 스캐닝 하므로 INDEX 힌트와 동일하다. [형식] /*+ INDEX_ASC(테이블명 [인덱스명 [인덱스명] … ]) */ Hints For Access Paths(INDEX_DESC)  INDEX, INDEX_ASC 힌트의 반대로 인덱스 영역에서 생성된 인덱스의 역순으로 스캐닝 하라는 의미로 데이터 값을 역순 정렬하라는 의미는 아니다. 인덱스가 생성될 때 내림차순으로 생성 되었다면 이 힌트를 사용한다면 데이터 값은 오름차순으로 나타나게 된다. [형식] /*+ INDEX_DESC(테이블명 [인덱스명 [인덱스명] … ]) */
Views: 185 이종철
DBMS - Index and Index Structure
 
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DBMS - Index and Index Structure Watch more Videos at https://www.tutorialspoint.com/videotutorials/index.htm Lecture By: Mr. Arnab Chakraborty, Tutorials Point India Private Limited
ADS1: Ordered structures for indexing
 
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We discuss a particular ordered data structure for indexing k-mers from a DNA string. Course page: https://www.coursera.org/course/ads1.
Views: 2121 Ben Langmead
How Does the Phyiscal Location of Rows Affect Indexes?: Finding All the Red Sweets Part 2
 
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In part one of the red candy series, Chris compared the efficiency of using a index range scan and full table scan to access data. He found that a full table scan was more efficient when fetching more rows than there are table blocks. This analysis made a big assumption however. It worked on the presumption that there was no correlation between the order of candies in the document and which the bags they were in. In this episode tests this assumption. Chris looks at how the physical order of rows in a table can affect the efficiency of indexes on it. He discusses how Oracle tracks this via the clustering factor. ============================ The Magic of SQL with Chris Saxon 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: 3369 The Magic of SQL
What is BLOCK RANGE INDEX? What does BLOCK RANGE INDEX mean? BLOCK RANGE INDEX meaning
 
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What is BLOCK RANGE INDEX? What does BLOCK RANGE INDEX mean? BLOCK RANGE INDEX meaning - BLOCK RANGE INDEX definition - BLOCK RANGE INDEX explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ A Block Range Index or BRIN is a database indexing technique. They are intended to improve performance with extremely large tables. BRIN indexes provide similar benefits to horizontal partitioning or sharding but without needing to explicitly declare partitions. A BRIN is applicable to an index on a table that is large and where the index key value is easily sorted and evaluated with a MinMax function. BRIN were originally proposed by Alvaro Herrera of 2ndQuadrant in 2013 as 'Minmax indexes'. Implementations thus far are tightly coupled to internal implementation and storage techniques for the database tables. This makes them efficient, but limits them to particular vendors. So far PostgreSQL is the only vendor to have announced a live product with this specific feature, in PostgreSQL 9.5. Other vendors have described some similar features, including Oracle, Netezza 'zone maps', Infobright 'data packs', MonetDB and Apache Hive with ORC/Parquet. BRIN operate by "summarising" large blocks of data into a compact form, which can be efficiently tested to exclude many of them from a database query, early on. These tests exclude a large block of data for each comparison. By reducing the data volume so early on, both by representing large blocks as small tuples, and by eliminating many blocks, BRIN substantially reduce the amount of detailed data that must be examined by the database node on a row-by-row basis. Data storage in large databases is layered and chunked, with the table storage arranged into 'blocks'. Each block contains perhaps 1MB in each chunk and they are retrieved by requesting specific blocks from a disk-based storage layer. BRIN are a lightweight in-memory summary layer above this: each tuple in the index summarises one block as to the range of the data contained therein: its minimum and maximum values, and if the block contains any non-null data for the column(s) of interest. Unlike a traditional index which locates the regions of the table containing values of interest, BRIN act as "negative indexes", showing the blocks that are definitely not of interest and thus do not need to be processed further. Some simple benchmarks suggest a five-fold improvement in search performance with an index scan, compared to the unindexed table. Compared to B-trees, they avoid their maintenance overhead. As BRIN are so lightweight, they may be held entirely in memory, thus avoiding disk overhead during the scan. The same may not be true of B-tree: B-tree requires a tree node for every approximately N rows in the table, where N is the capacity of a single node, thus the index size is large. As BRIN only requires a tuple for each block (of many rows), the index becomes sufficiently small to make the difference between disk and memory. For a 'narrow' table the B-tree index volume approaches that of the table itself; the BRIN may be only 5-15% of it. A large database index would typically use B-tree algorithms. BRIN is not always a substitute for B-tree, it is an improvement on sequential scanning of an index, with particular (and potentially large) advantages when the index meets particular conditions for being ordered and for the search target to be a narrow set of these values. In the general case, with random data, B-tree may still be superior. A particular advantage of the BRIN technique, shared with Oracle Exadata's Smart Scanning, is in the use of this type of index with Big Data or data warehousing applications, where it is known that almost all of the table is irrelevant to the range of interest. BRIN allows the table to be queried in such cases by only retrieving blocks that may contain data of interest and excluding those which are clearly outside the range, or contain no data for this column. A regular problem with the processing of large tables is that retrieval requires the use of an index, but maintaining this index slows down the addition of new records. Typical practices have been to group additions together and add them as a single bulk transaction, or to drop the index, add the batch of new records and then recreate the index. Both of these are disruptive to simultaneous read / write operations and may not be possible in some continuously-operating businesses. With BRIN, the slowdown from maintaining the index is much reduced compared to B-tree. Wong reports that B-tree slowed down additions to an unindexed 10GB table by 85%, but a comparable BRIN only had an overhead of 11%. BRIN may be created for extremely large data where B-tree would require horizontal partitioning.....
Views: 264 The Audiopedia
Oracle tutorial : Collection in Oracle PL SQL -  Varray
 
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Oracle tutorial : Collection in Oracle PL SQL Varray . oracle tutorial for beginners 1)Varray provide feature of data structure in Oracle. 2)It can store a fixed-size sequential collection of elements of the same type. 3)This is used to store the ordered collection of data. 4)According to its structure the varray consist of contiguous memory locations. 5)The address is start from lowest to highest. 6)It start to store element from lowest address to highest address. 7)The starting index for varray is 1. 8)This is an one-dimensional array. Syntax : CREATE OR REPLACE TYPE varray_type_name IS VARRAY(n) of element_type DECLARE CURSOR cur_employee is SELECT NAME FROM employee; type emp_list is varray (10) of employee.name%type; empname_list emp_list := emp_list(); mycount integer :=0; BEGIN FOR i IN cur_employee LOOP mycount := mycount + 1; empname_list.extend; empname_list(mycount) := i.name; dbms_output.put_line('Employee Nane -'||empname_list(mycount)); END LOOP; END; / https://techquerypond.com , https://techquerypond.wordpress.com https://twitter.com/techquerypond
Views: 1483 Tech Query Pond
SQL Server 33 - Indexes
 
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Indexes allow us to tell the database that certain columns are columns we want to retrieve commonly. This allows the database to optimize retrieval. Additionally, when we get into the SELECT statement, we will often have to join data from multiple tables. When we correctly add indexes to our tables, we can improve the speed of our SELECT and also our joins. There are two types of Index. One is called clustered and the other is called non-clustered. Clustered indexes determine the actual order of the table. By default this is going to be the primary key column. So when you label a column as PRIMARY KEY, you are also going to be creating an INDEX that is a clustered index. A clustered index is kind of like a telephone book, where the data is right there when you look up a phone number. This means that if you are just making a small database that is only going to store a few things, you may be fine. But more likely than not you are going to want to add additional indexes. When you add a new index, you create a non-clustered index. These things do not actually determine the order of the rows in the table. A way of how you can think of how these work is like an index in the back of a book. The index of the book does not actually contain the data, it just tells you where to find it. What columns do you index? You are going to want every primary key to be indexed. What about foreign keys, are they indexed by default? No, they are not. Of all columns, you are probably going to want to index the foreign keys the most because they are used in joins. Lastly, you will likely want to index columns that you are going to use on a regular basis. You can also make composite indexes just like you can make composite keys. You would want to do this when you are going to constantly being using those columns together. There is a lot to learn on multicolumn indexes. We may explore this concept in more detail and see how SQL Server uses them in a future video, but as of right now it's probably more important that we get a general understanding of all things SQL Server before we deep dive on something like that. In the upcoming videos I'll be teaching you how to create indexes. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Support me! http://www.patreon.com/calebcurry Subscribe to my newsletter: http://bit.ly/JoinCCNewsletter Donate!: http://bit.ly/DonateCTVM2. ~~~~~~~~~~~~~~~Additional Links~~~~~~~~~~~~~~~ More content: http://CalebCurry.com Facebook: http://www.facebook.com/CalebTheVideoMaker Google+: https://plus.google.com/+CalebTheVideoMaker2 Twitter: http://twitter.com/calebCurry Amazing Web Hosting - http://bit.ly/ccbluehost (The best web hosting for a cheap price!)
Views: 11362 Caleb Curry
Why Indexing is used | Indexing Beginning | DBMS
 
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This video explains Why we need indexing from very basics. Concept of indexing is very important for GATE UGC NET and specially Interviews.
Views: 8789 Gate Smashers
A Story of Index Only Scans: Finding all the Red Sweets Part 3
 
05:25
So far in the red candy series, Chris has compared using an index to a full table scan to access sweets from his table. In this video he asks a different question: What if you just want to count how many sweets are red? In this case the index holds all the information Oracle needs to answer the query. He shows how the optimizer is able to process this via an index only scan. Chris goes on to investigate index only scans further. He discusses how theses can provide better performance than queries accessing the table itself. He finishes by looking at the conditions necessary to enable these. ============================ The Magic of SQL with Chris Saxon 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: 1782 The Magic of SQL
Learning Apache Cassandra : Primary Key and Cluster Ordering | packtpub.com
 
05:31
This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2jcNLke]. In this video, we will see what a primary key is. • Learn what a clustering key is • How to model data using primary and clustering key For the latest Big Data and Business Intelligence tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 1155 Packt Video
PART 5.5 Primary Indexing | DBMS HINDI |
 
08:39
Thank you friends for watching the video. Please Like the video if it has helped you in any way & do subscribe to the channel. This video contains the detail discussion of primary indexing in dbms with example. Detail explanation of Primary Indexing, Example of primary indexing, How Primary indexing works in dbms, Properties of Primary Indexing in dbms, Properties of single level indexing, Questions of Primary Indexing,Advantages of Primary Indexing,Numericals on primary Indexing for gate exam, How primary indexing works on file is explained. PRIMARY INDEXING- i) Main file is always sorted according to primary key. ii) Indexing is done on Primary Key, therefor called as primary indexing iii) Index file have two columns, first primary key and second anchor pointer(base address of block) iv) It is an example of Sparse Indexing. v) Here first record(anchor record) of every block gets an entry in the index file vi) No. of entries in the index file = No of blocks acquired by the main file. vii) No. of access required= log2n +1, where n=no. of blocks acquired by the index file. Please spare some time and fill this form so that we can know about you and what you think about us: https://goo.gl/forms/b5ffxRyEAsaoUatx2 Your review/recommendation and some words can help validating our quality of content and work.. so Please do the following: - 1) Give us a 5 star review with comment on Google https://goo.gl/maps/sLgzMX5oUZ82 2) Follow our Facebook page and give us a 5 star review with comments https://www.facebook.com/pg/knowledgegate.in/reviews 3) Follow us on Instagram https://www.instagram.com/mail.knowledgegate/ DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,Partial Dependency, Multivalued dependency,Indexing,Hashing, B tree,B+ tree,Ordered Indexing,Select operation,Join operations, Natural joins, SQL commands,File structure in DBMS,Primary Indexing,Clustered Indexing,Concurrency control protocols, Transaction Management in DBMS,ACID properties, Data Consistency, Concurrency in database,Deadlock in database, Deadlock handling, Database Recovery, Deadlock avoidance, Deadlock prevention,Scheduling in dbms, Conflict Serializability, Serial Schedules, Two phase locking,SQL commands,DBMS for gate , DBMS for net, DBMS lectures, DBMS tutorials, DBMS for beginners, learn DBMS, Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Primary Indexing in DBMS,numerical of primary indexing in dbms, solved question of primary indexing in dbms,indexing in dbms tutorial for Gate, Net hindi, Indexing in dbms, Indexing in dbms tutorial in hindi,about indexing in dbms,indexing and hashing in dbms, terminologies in indexing in database,indexing in dbms example,indexing in dbms tutorial,disadvantages of indexing in dbms,indexing in dbms for gate, sparse indexing example, dense indexing in dbms example,Primary Indexing in DBMS,numerical of primary indexing in dbms, solved question of primary indexing in dbms,indexing in dbms tutorial for Gate, Net hindi, DBMS blueprint, DataBase Management system,database,DBMS, RDBMS, Relations, Table, Query, Normalization, Normal forms,Database design,Relational Model,Instance,Schema,Data Definition Language, SQL queries, ER Diagrams, Entity Relationship Model,Constraints,Entity,Attributes,Weak entity, Types of entity,DataBase design, database architecture, Degree of relation,Cardinality ratio,One to many relationship,Many to many relationships,Relational Algebra,Relational Calculus, Tuples, Natural Join, Join operations,Database Architecture,database Schema, Keys in DBMS, Primary keys, Candidate keys, Foreign keys,Data redundancy, Duplicacy in data, Data Inconsistency, Normalization, First Normal Form,Second Normal Form, third normal forms, Boye codd's normal form,1NF,2NF,3NF,BCNF, Normalization rules, Decomposition of relation, Functional Dependency,Partial Dependency,
Views: 83870 KNOWLEDGE GATE
SQL Partition By Explained
 
06:42
Using Oracle's SQL, I'll explain how to use Partition By. This will be similar in other SQL engines that have the Partition By keyword.
Views: 31962 Pretty Printed
What is an Index - Database Tutorial 8
 
13:33
Database Tutorial. This video is about Database Fundamentals. I hope this series of videos can help those who want to be Database Professionals. I will cover various database technologies including Oracle Database, Microsoft SQL Server database and Sybase. Video: What is an Index (Video 8 in the Database Tutorial Series)
Views: 113610 Sam Dhanasekaran
SQL - Multisets, Distinct operator, Set Operators & String Comparison
 
24:07
For Complete Video Series visit http://www.studyyaar.com/index.php/module/14-sql More Learning Resources and Full videos are only available at www.studyyaar.com This video clip is part of module available at http://www.studyyaar.com/index.php/learning-program/2-database-management-system-part-1
Views: 1984 StudyYaar.com
(오라클힌트교육,SQL튜닝)오라클힌트를 이용한 쿼리 튜닝, 중첩루프조인유도힌트, oracle hint/ordered/use nl_
 
09:24
Hints for Join Orders(USE_NL) - USE_NL 힌트는 테이블을 조인 하는 경우 중첩 루프 조인(Nested Loop Join)이 일어나도록 하는 힌트 문장이다. 중첩 루프 조인은 중첩반복 이라고도 하는데 하나의 테이블(outer/driving table)에서 추출된 ROW를 가지고 일일이 다른 테이블(inner/probed table)을 반복해서 조회하여 찾아지는 레코드를 최종 데이터로 간주하는 방법 이다. - EMP 테이블과 DEPT 테이블을 조인하는 경우 DEPT 테이블이 건수가 작다면 우선 이 테이블을 외부 루프로 해서 하나씩 읽으면서 이에 대응하는 EMP 테이블의 데이터를 추출 하는 경우가 중첩 루프 조인에 해당 한다. 이때 EMP 테이블의 경우 대부분 조인 칼럼에 인덱스를 이용하는 것이 성능상 좋다. 즉 중첩 루프 조인은 테이블 중 적어도 하나의 조인 컬럼에 대해 인덱스(or Hash Index)가 존재할 때 연관되는 방식으로 이 중첩 루프 조인에서 테이블 중 하나의 테이블 또는 중간 결과 셋을 대상으로 FULL SCAN이 일어나게 된다.  보통 USE_NL 힌트 구문은 ORDERED 힌트 구문과 같이 사용되는데 USE_NL이 취하는 인자는 FROM절에서 두 번째 나오는 테이블(비드라이빙 테이블, inner/probed table)을 명시해 주어야 한다. 인수로 사용되지 않은 첫 번째 테이블이 드라이빙 테이블(outer table)이 된다. Hints for Join Orders(ORDERED)  힌트는 FROM 뒤에 기술되는 테이블의 순서대로 조인이 일어나도록 해주는 구문이며 대부분 단독으로는 사용되지 않고 USE_NL(중첩 루프 조인을 유도), USE_MERGE(머지 소트 조인을 유도), USE_HASH(HASH 조인을 유도)등과 같이 사용된다.  USE_NL/USE_MERGE/USE_HASH등의 인자로 사용되는 테이블은 FROM절에서 두 번째로 나타나는 테이블 이어야 하는데 FROM절에서 처음 나타나는 테이블이 드라이빙 테이블(OUTER/DRIVING TABLE)이 되고 나중에 나타나는 테이블이 PROBED TABLE(INNER TABLE)이 된다. 보통 드라이빙 테이블의 경우 데이터 건수가 적거나 조인 칼럼에 대해 인덱스가 없는 테이블이 주로 사용된다.  중첩 루프 조인(Nested Loop Join)이나 해시조인(Hash Join)의 경우 성능이 FROM절 뒤에 나타나는 테이블의 순서에 영향을 받지만 MERGE 조인은 영향을 받지 않는다. 머지 조인은 메모리에 올려서 정렬 시킨 후 병합하니까 실행 계획은 다르게 나올지 모르지만 성능에는 관계 없다.
Views: 209 이종철
Hierarchical Queries: Databases for Developers #16
 
09:38
Often data contains a parent-child relationship between rows in the same table. For example, company org charts and family trees. You can use the power of SQL to traverse these hierarchical relationships. There are two ways to do this in Oracle Database: - Connect By - Recursive With Watch this video to learn about data trees and find out how these work! Further reading: Hierarchical queries in the docs: https://docs.oracle.com/en/database/oracle/oracle-database/18/sqlrf/Hierarchical-Queries.html#GUID-0118DF1D-B9A9-41EB-8556-C6E7D6A5A84E Recursive subquery factoring in 11.2: https://oracle-base.com/articles/11g/recursive-subquery-factoring-11gr2 Take the course! https://devgym.oracle.com/pls/apex/dg/class/databases-for-developers-next-level.html Need help with SQL? Ask us over on AskTOM: https://asktom.oracle.com Twitter: https://twitter.com/ChrisRSaxon Daily SQL Twitter tips: https://twitter.com/SQLDaily All Things SQL blog: https://blogs.oracle.com/sql/ ============================ The Magic of SQL with Chris Saxon 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: 4086 The Magic of SQL
ORDER BY clause in SQL | Database Management System
 
06:56
Join discussion on: http://www.techtud.com/video-lecture/order-clause-sql IMPORTANT LINKS: 1) Official Website: http://www.techtud.com/ 2) Virtual GATE: http://virtualgate.in/login/index.php Both of the above mentioned platforms are COMPLETELY FREE, so feel free to Explore, Learn, Practice & Share! Our Social Media Links: Facebook Page: https://www.facebook.com/techtuduniversity Facebook Group: https://www.facebook.com/groups/virtualgate Google+ Page: https://plus.google.com/+techtud/posts Last but not the least, SUBSCRIBE our YouTube channel to stay updated about the regularly uploaded new videos.
Views: 5273 Techtud
Oracle interview question, Difference between Rank and Dense Rank
 
03:56
Oracle interview question Difference between Rank and Dense Rank Both RANK() and DENSK_RANK() function gives the ranking within the ordered partition of data, However if same rank is assigned to more than one record, then the next rank(s) will be skipped by RANK() function, whereas, the ranks are consecutive for DENSE_RANK. No ranks will be skipped in case of DENSE_RANK even if more than one row are assigned with same rank. List of all the SQL and PLSQL interview questions https://easy-learning-tech.blogspot.com/p/oracle-sql-plsql-interview-questions.html
Views: 449 Siva Academy
Unordered/Sorted/Hashed Files, Indexes
 
33:35
Database Management Systems 5. Unordered/Sorted/Hashed Files, Indexes ADUni
Views: 3736 Chao Xu
DBMS Implementation - DataBase Management Systems Implementation Techniques
 
01:20:30
DBMS Implementation - DataBase Management Systems Implementation Techniques DBMS Interview Questions and Answers: https://www.wikitechy.com/interview-questions/dbms/ Contents: 1. RAID RAID Levels to use of Disk Arrays 2. File Organization Heap File Organization Sequential File Organization Hash File Organization Clustered File Organization 3. Ordered Indices Primary Index Secondary Index 4. B+ Tree Index Files B+ Tree Insertion B+ Tree Deletion 5. B Tree Index Files 6. Static Hashing Operation of Static hashing 7. Dynamic Hashing Operation of Dynamic hashing 8. Query Processing Overview Basic Steps in Query Processing 9. Algorithm for Select and Join operations Algorithm for Select Join Operations 10. Query Optimization For More Interview Questions and Answers visit https://www.wikitechy.com/interview-questions-and-answers HR Interview Questions and Answers visit https://www.wikitechy.com/hr-interview-questions/ 800+ Resumes Samples for Freshers and Experienced visit https://www.wikitechy.com/resume/ Programming tutorials visit https://www.wikitechy.com/online-tutorials Free Final Year Projects visit https://www.wikitechy.com/projects Tricks and Tips visit https://www.wikitechy.com/technology/ Ask Questions at https://forums.wikitechy.com/ Follow us on following Social Networks http://Facebook.com/wikitechy catch us on Facebook http://instagram.com/wikitechycom catch us on Instagram http://Twitter.com/wikitechycom follow us on Twitter https://plus.google.com/+Wikitechy - Catch us on Google Plus All content used is copyright of Wikitechy Use or commercial display or editing of the content without proper authorization is not allowed. #dbms #db #sql #database
Views: 406 KaaShiv Venkat
SQL Server Columnstore Index Performance Demonstration
 
04:18
This video presents a demonstration of the level of query performance that can be achieved for data warehouses and data marts in SQL Server Denali with the new columnstore index and enhanced query execution capability. Performance in this demonstration when using a columnstore index improves on the order of a stunning 50 times for a single query. This is for the same data on the same hardware, compared to the previous release of SQL Server when running the query over a fact table stored in a PAGE-compressed clustered B-tree index ordered by date. The bottom line is that users will get more business value out of their data and make better decisions with columnstore indexes in SQL Server because they can explore data much more interactively.
Views: 530 MicrosoftBI
types of indexing in dbms | dbms indexing gate | DBMS Lectures in Hindi #86
 
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Welcome to series of gate lectures by well academy types of indexing in dbms | Classification of index | DBMS Lectures in Hindi #86 GATE Practice Book Purchase Link ( ACE Academy ) https://goo.gl/jESdtD GATE Practice Book Purchase Link ( Made Easy ) https://goo.gl/zUU5Vn DBMS Gate Lectures Full Course FREE Playlist : https://goo.gl/Z7AAyV Facebook Me : https://goo.gl/2zQDpD Click here to subscribe well Academy https://www.youtube.com/wellacademy1 GATE Lectures by Well Academy Facebook Group https://www.facebook.com/groups/1392049960910003/ Thank you for watching share with your friends Follow on : Facebook page : https://www.facebook.com/wellacademy/ Instagram page : https://instagram.com/well_academy Twitter : https://twitter.com/well_academy dbms indexing, dbms indexing gate, dbms indexing in hindi, indexing in dbms in hindi, file indexing in dbms, indexing in dbms in hindi, indexing in dbms with examples, types of indexing in dbms, dbms indexing gate, dbms indexing, dbms indexing gate, dbms indexing in hindi, indexing in dbms in hindi, indexing structures in dbms, indexing in dbms, indexing in dbms for gate, indexing in dbms in english, multilevel indexing in dbms,
Views: 8765 Well Academy
DBMS - Ordering Tuples in SQL
 
03:49
DBMS - Ordering Tuples in SQL Watch more Videos at https://www.tutorialspoint.com/videotutorials/index.htm Lecture By: Mr. Arnab Chakraborty, Tutorials Point India Private Limited
Row Number function in SQL Server
 
07:24
sql server row_number example sql server row number by partition sql server row_number over partition by order by In this video we will discuss Row_Number function in SQL Server. This is continuation to Part 108. Please watch Part 108 from SQL Server tutorial before proceeding. Row_Number function Introduced in SQL Server 2005 Returns the sequential number of a row starting at 1 ORDER BY clause is required PARTITION BY clause is optional When the data is partitioned, row number is reset to 1 when the partition changes Syntax : ROW_NUMBER() OVER (ORDER BY Col1, Col2) Row_Number function without PARTITION BY : In this example, data is not partitioned, so ROW_NUMBER will provide a consecutive numbering for all the rows in the table based on the order of rows imposed by the ORDER BY clause. SELECT Name, Gender, Salary, ROW_NUMBER() OVER (ORDER BY Gender) AS RowNumber FROM Employees Please note : If ORDER BY clause is not specified you will get the following error The function 'ROW_NUMBER' must have an OVER clause with ORDER BY Row_Number function with PARTITION BY : In this example, data is partitioned by Gender, so ROW_NUMBER will provide a consecutive numbering only for the rows with in a parttion. When the partition changes the row number is reset to 1. SELECT Name, Gender, Salary, ROW_NUMBER() OVER (PARTITION BY Gender ORDER BY Gender) AS RowNumber FROM Employees Use case for Row_Number function : Deleting all duplicate rows except one from a sql server table. Discussed in detail in Part 4 of SQL Server Interview Questions and Answers video series. Text version of the video http://csharp-video-tutorials.blogspot.com/2015/09/rownumber-function-in-sql-server.html Slides http://csharp-video-tutorials.blogspot.com/2015/09/rownumber-function-in-sql-server_30.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: 85561 kudvenkat
Top-N Queries Against an Oracle Database
 
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A demonstration of how to perform Top-N queries against an Oracle Database, including the new row limiting clause in Oracle Database 12c. For more information see: https://oracle-base.com/articles/misc/top-n-queries https://oracle-base.com/articles/12c/row-limiting-clause-for-top-n-queries-12cr1 Website: https://oracle-base.com Blog: https://oracle-base.com/blog Twitter: https://twitter.com/oraclebase Cameo by Debra Lilley Blog: http://debrasoracle.blogspot.co.uk Twitter: https://twitter.com/debralilley Cameo appearances are for fun, not an endorsement of the content of this video.
Views: 8190 ORACLE-BASE.com
22 - Основы java. Коллекции
 
16:41
Лектор: Тимур Батыршинов (http://javabegin.ru). Ссылки из урока: http://docs.oracle.com/javase/8/docs/technotes/guides/collections/changes8.html http://docs.oracle.com/javase/tutorial/collections/interfaces/index.html
Views: 11137 Roman Brovko
Oracle || PL/SQL Argument/Parameter Type  Part - 2 by dinesh
 
13:59
DURGASOFT is INDIA's No.1 Software Training Center offers online training on various technologies like JAVA, .NET , ANDROID,HADOOP,TESTING TOOLS ,ADF,INFORMATICA,TABLEAU,IPHONE,OBIEE,ANJULAR JS, SAP... courses from Hyderabad & Bangalore -India with Real Time Experts. Mail us your requirements to [email protected] so that our Supporting Team will arrange Demo Sessions. Ph:Call +91-8885252627,+91-7207212428,+91-7207212427,+91-8096969696. http://durgasoft.com http://durgasoftonlinetraining.com https://www.facebook.com/durgasoftware http://durgajobs.com https://www.facebook.com/durgajobsinfo......
Sorting in Descending Order in SQL Using Order By Desc Clause - SQL LESSON 29
 
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Sorting in Descending Order in SQL Using Order By Desc Clause - SQL LESSON 29
Views: 16994 HandsonERP
Difference between rank dense rank and row number in SQL
 
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row_number vs rank vs dense_rank in sql server dense_rank vs rank vs row_number sql server rank dense_rank row_number in sql server In this video we will discuss the similarities and difference between RANK, DENSE_RANK and ROW_NUMBER functions in SQL Server. Similarities between RANK, DENSE_RANK and ROW_NUMBER functions Returns an increasing integer value starting at 1 based on the ordering of rows imposed by the ORDER BY clause (if there are no ties) ORDER BY clause is required PARTITION BY clause is optional When the data is partitioned, the integer value is reset to 1 when the partition changes 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', 6000) Insert Into Employees Values (2, 'John', 'Male', 8000) Insert Into Employees Values (3, 'Pam', 'Female', 4000) Insert Into Employees Values (4, 'Sara', 'Female', 5000) Insert Into Employees Values (5, 'Todd', 'Male', 3000) Notice that no two employees in the table have the same salary. So all the 3 functions RANK, DENSE_RANK and ROW_NUMBER produce the same increasing integer value when ordered by Salary column. SELECT Name, Salary, Gender, ROW_NUMBER() OVER (ORDER BY Salary DESC) AS RowNumber, RANK() OVER (ORDER BY Salary DESC) AS [Rank], DENSE_RANK() OVER (ORDER BY Salary DESC) AS DenseRank FROM Employees You will only see the difference when there ties. Now let's include duplicate values for Salary column. To do this First delete existing data from the Employees table DELETE FROM Employees Insert new rows with duplicate valuse for Salary column Insert Into Employees Values (1, 'Mark', 'Male', 8000) Insert Into Employees Values (2, 'John', 'Male', 8000) Insert Into Employees Values (3, 'Pam', 'Female', 8000) Insert Into Employees Values (4, 'Sara', 'Female', 4000) Insert Into Employees Values (5, 'Todd', 'Male', 3500) Notice 3 employees have the same salary 8000. When you execute the following query you can clearly see the difference between RANK, DENSE_RANK and ROW_NUMBER functions. SELECT Name, Salary, Gender, ROW_NUMBER() OVER (ORDER BY Salary DESC) AS RowNumber, RANK() OVER (ORDER BY Salary DESC) AS [Rank], DENSE_RANK() OVER (ORDER BY Salary DESC) AS DenseRank FROM Employees Difference between RANK, DENSE_RANK and ROW_NUMBER functions ROW_NUMBER : Returns an increasing unique number for each row starting at 1, even if there are duplicates. RANK : Returns an increasing unique number for each row starting at 1. When there are duplicates, same rank is assigned to all the duplicate rows, but the next row after the duplicate rows will have the rank it would have been assigned if there had been no duplicates. So RANK function skips rankings if there are duplicates. DENSE_RANK : Returns an increasing unique number for each row starting at 1. When there are duplicates, same rank is assigned to all the duplicate rows but the DENSE_RANK function will not skip any ranks. This means the next row after the duplicate rows will have the next rank in the sequence. Text version of the video http://csharp-video-tutorials.blogspot.com/2015/10/difference-between-rank-denserank-and.html Slides http://csharp-video-tutorials.blogspot.com/2015/10/difference-between-rank-denserank-and_2.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: 43207 kudvenkat
오라클 힌트 강좌#4, HASH조인의 이해와 ORDERED, USE_HASH힌트를 이용한 해시조인유도와 조인시 드라이빙 테이블의 선정을 위한 오라클 힌트 강좌
 
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오라클 힌트 강좌#4, HASH조인의 이해와 ORDERED, USE_HASH힌트를 이용한 해시조인유도와 조인시 드라이빙 테이블의 선정을 위한 오라클 힌트 강좌 해시조인 이란? 해시조인을 위한 USE_HASH 힌트의 이해 ORDERED, LEADING 힌트를 통한 해시 조인시 드라이빙 테이블(Build Input)의 선정
Views: 248 이종철
Part 8   SQL Query to find department with highest number of employees
 
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Link for all dot net and sql server video tutorial playlists http://www.youtube.com/user/kudvenkat/playlists Link for slides, code samples and text version of the video http://csharp-video-tutorials.blogspot.com/2014/06/part-8-sql-query-to-find-department.html Scenario asked in the SQL Server Interview Based on the above two tables write a SQL Query to get the name of the Department that has got the maximum number of Employees. To answer this question it will be helpful if you the knowledge of JOINS & GROUP BY in SQL Server. We discusses these in Parts 11 & 12 of SQL Server Tutorial video series. SQL query that retrieves the department name with maximum number of employees SELECT TOP 1 DepartmentName FROM Employees JOIN Departments ON Employees.DepartmentID = Departments.DepartmentID GROUP BY DepartmentName ORDER BY COUNT(*) DESC Scenario asked in the SQL Server Interview Based on the above two tables write a SQL Query to get the name of the Department that has got the maximum number of Employees. To answer this question it will be helpful if you the knowledge of JOINS & GROUP BY in SQL Server. We discusses these in Parts 11 & 12 of SQL Server Tutorial video series. SQL query that retrieves the department name with maximum number of employees SELECT TOP 1 DepartmentName FROM Employees JOIN Departments ON Employees.DepartmentID = Departments.DepartmentID GROUP BY DepartmentName ORDER BY COUNT(*) DESC
Views: 125934 kudvenkat
Dense Indexing - Basis Data
 
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Kenapa google bisa cepat sekali menampilkan hasil pencarian? Kenapa kamu bisa melihat daftar barang di Amazon, Bukalapak, Tokopedia dengan cepat? Nah, pada video kali ini kita akan mengulas teknik mempercepat menampilkan data yaitu Indexing. Apa itu indexing, konsep dan contohnya ketika SQL dieksekusi dibahas lengkap pada video ini. Video kuliah: Basis Data Bab: Indexing Topik Bahasan: Ordered Indices Pokok Bahasan: Dense Indexing Tautan video: https://youtu.be/QWl2biDpZhw Video terkait: Cara kerja indeks: https://youtu.be/Sbk8LsU9R6M (c) 2018 - Program Studi Teknik Informatika - Universitas Ahmad Dahlan
Views: 221 Ardiansyah MCs
Java Collections Tutorial for Beginnners | (All concepts in Single Video)
 
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Java Collections Framework: What is an Iterator? → An iterator over a collection → Iterators allow the caller to remove elements from the underlying collection during the iteration with well-defined semantics. Iterator Interface: → Iterator Interface is a member of Java Collections Framework. What is List? → A List is an ordered Collection → Lists may contain duplicate elements → Positional Access - Manipulates elements based on their numerical position in the list → Search - Searches for a specified object in the list and returns its index position What is ArrayList? → Dynamic array for storing the elements → Inherits the AbstractList → Implements List interface → Can contain duplicate elements → Maintains insertion order → Non synchronized → Allows random access What is LinkedList? → Doubly linked list to store the elements → Inherits the AbstractList → Implements List and Deque interfaces → Can contain duplicate elements → Maintains insertion order → Non synchronized → Manipulation is fast because no shifting needs to be occurred What is HashMap? → Implements the map interface → HashMap contains values based on the key → Contains only unique elements → May have one null key and multiple null values → Maintains no order What is stack? → Stack is a subclass of Vector → It implements a standard last-in, first-out stack → It has only default constructor What is Vector? → Implements a dynamic array → Vector is synchronized → Vector contains many legacy methods → Can dynamically change the size of a Vector at runtime. What is LinkedHashMap? → Implements Map Interface → Stores key/value pairs in insertion order → Contains values based on key → Contains only unique elements → Can have one null key → Can have multiple null values What is TreeMap? → Implements Map Interface → Stores key/value pairs in sorted order → Contains values based on key → Contains only unique elements → Cannot have null key → Can have multiple null values TreeMap: → Implemented based on red-black tree structure → Ordered by the key What is HashTable? → Hashtable was part of the original java.util → Concrete implementation of a Dictionary → Java 2 re-engineered Hashtable so that it also implements the Map interface → Hashtable stores key/value pairs in a hash table HashMap vs LinkedHashMap vs TreeMap HashMap: → Implemented as a hash table,vi → No ordering on keys or values LinkedHashMap: → Insertion order For more details & source code check out: http://www.letsmakelearningsimple.com/2019/02/java-collections-framework.html #javacollections #java #letsmakelearningsimple #rakesh #rake ******************************************************* IMPORTANT PLAYLISTS: Java course tutorial: Tamil: https://www.youtube.com/playlist?list=PLN00Qh4gtjNvXIWBwL3MxbAdQMe9xhpTy Telugu: https://www.youtube.com/playlist?list=PLN00Qh4gtjNtyEZ_b-EVZNcQIMmhov-mH English: https://www.youtube.com/playlist?list=PLN00Qh4gtjNvty8ynSn9_3iOTDSe3gzoa Software Design Patterns course tutorial: Tamil: https://www.youtube.com/playlist?list=PLN00Qh4gtjNspk6zNQbCXnF3gsImfNym_ Telugu: https://www.youtube.com/playlist?list=PLN00Qh4gtjNv2L1bRnNEZNDbBVLYEpeUe English: https://www.youtube.com/playlist?list=PLN00Qh4gtjNt1mk67B4rQf244F4Fzz6nU ******************************************************* Subscribe my YouTube channels: ►Subscribe http://bit.ly/2HNPJGe this channel for watching Software Related courses like Java, Software Design Patterns, OOPs, and etc in Tamil, Telugu, and English. ►Subscribe http://bit.ly/2TsDz7c this channel for watching Income Tax saving schemes and Stock Market related videos. ►Subscribe http://bit.ly/2RwqfNq this channel for watching Terrace Gardening Tips, Unboxing products, and Random videos in Tamil, Telugu, and English. Website: www.letsmakelearningsimple.com FaceBook page: https://www.facebook.com/letsmakelearningsimple/ Instagram: https://www.instagram.com/lets_make_learning_simple Twitter: https://twitter.com/LMLS ******************************************************* Check out http://bit.ly/2E9P8el for complete SOFTWARE TUTORIAL COURSES: Check out http://bit.ly/2N52TxG for buying BEST SOFTWARE TUTORIAL BOOKS DISCLAIMER: This video and description contains affiliate links, which means that if you click on one of the product links, I’ll receive a small commission. This helps support the channel and allows us to continue to make videos like this. Thank you for the support!
Index Meaning Definition Pronunciation Example Synonym Antonyms
 
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This video explain about the meaning, definition, pronunciation of the word Index with examples and few synonyms and antonyms. Index Meaning of Index Index This video explain about the meaning, definition, pronunciation of the word Index with examples and few synonyms and antonyms. Index Meaning of Index An index is a system by which changes in the value of something and the rate at which it changes can be recorded, measured, or interpreted. An alphabetical list of names, subjects, etc. with reference to the pages on which they are mentioned Let's see some examples of Index The librarian keeps an alphabetical index that lists all of the novels that can be found on the first two shelves. Books in the library are indexed by author, title, subject, and key word. Their Internet site offers an index of the news stories of the past year. Previous video: https://youtu.be/uumNgGRJpEM Next video: https://youtu.be/MRgGyS4vjv4
Shopping Cart with PHP and MySQL - Updating Quantity and Saving Orders
 
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In this video, I will demo how to Update Quantity and Saving Orders in Shopping Cart with PHP and MySQL To download all sources code for this demo please pay for me $5 at my PayPal Account: [email protected] ====================================================== You can see and download source code demo from my Apps at https://play.google.com/store/apps/developer?id=PMK+Lab ====================================================== You also can buy my apps in http://codecanyon.net/user/octopuscodes/portfolio ====================================================== You also can read my blog in http://learningprogramming.net/ ====================================================== You also can learn Microsoft Office in https://www.youtube.com/channel/UCFrMOR6KF4cpa92OOPRyOng ====================================================== TODAY IS A GREAT DAY TO LEARN SOMETHING NEW! ====================================================== Finding Software videos help you watch reviews for Open Sources:Joomla, wordpress, drupal, magento, html template, free admin template, free bootstrap admin templates, SilverStripe, Cake PHP, CodeIgniter, Concrete5, Modx, ExpressionEngine, Alfresco,TYPOlight, laravel, magento, angularjs, node.js, html, css, javascript, jquery, java, .net, wamp server, xampp, php, mysql, sql server, oracle, open sources, android, hibernate, jpa, html5, jquery
Views: 48710 Learning Programming
SQL Tutorial - 06 - Select - Where, Limit, Distinct, Order by
 
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This SQL tutorial lives at: http://www.pvtuts.com/sql/sql-select The video covers the SQL select statement and the where modifier.
Views: 23505 ProgrammingVideos
Oracle IoT Fleet Monitoring Overview by Srini Rajagopal (Oracle)
 
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Presentation by Srini Rajagopal during the OTM User Conference Europe in Amsterdam on 23 March 2018. In today’s world of intelligent and connected devices, people have an expectation of being able to track things in real-time. Whether you want to know the location of your Uber or Lyft driver, the pizza you just ordered, or simply make sure your kids are where they are supposed to be, all of this information is available at your fingertips and usually within seconds. Why should freight be any different? Oracle IoT Fleet Monitoring Cloud and Oracle Transportation Management Cloud make real-time shipment tracking a reality. Learn how this preconfigured solution eliminates the need for phone calls, emails, and other manual tasks, and pushes real-time shipment tracking information to you and your customers, saving you time, money, and improving customer service. Srini Rajagopal is Senior Director, Logistics Product Strategy at Oracle. He has responsibility for the team that leads the strategy for Oracle Transportation Management and Global Trade Management. Srini was part of the G-Log team and came to Oracle in 2005 as part of the G-Log acquisition. Presentation slides: https://otmsig.communities.oaug.org/index.php/calendar/icalrepeat.detail/2018/03/21/24/-/2018-otm-user-conference-europe#agenda More info: http://www.otmsig.com
Views: 731 OTMSIGchannel
Database index - Primary Index, Secondary Index, Dense Index, Sparse Index
 
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Complete set of Video Lessons and Notes available only at http://www.studyyaar.com/index.php/module/24-file-organization-and-database-index Index, Quality of an Index, Types of Index, Ordered Index, Primary Index- Def., Secondary Index- Def., Dense Index- Def., Sparse Index- Def., MultiLevel Index, Insertion in an Index, Deletion from an Index, Secondary Index http://www.studyyaar.com/index.php/module-video/watch/63-database-indexing
Views: 35390 StudyYaar.com