Employee Stock Ownership Plan Or ESOP - Muds ManagementMUDS Management & Strategic ServicesThe document outlines the Employee Stock Ownership Plan (ESOP) offered by Muds Management Pvt. Ltd., detailing its benefits to both employees and employers. It explains the process of granting and vesting ESOPs, eligibility criteria for participation, and required documentation for implementation. Additionally, it highlights the legal compliance aspects, including relevant acts and guidelines that must be followed.
TSQL in SQL Server 2012Eduardo CastroThe document discusses enhancements in SQL Server 'Denali', including new T-SQL features such as robust result set metadata discovery, improved error handling, and support for new data types. It highlights the introduction of file tables, sequence generators, and columnstore indexes, which significantly improve query performance by enabling efficient data compression. Additionally, it provides links to various resources for further reading on these topics.
Indian movies gamesAditya JadounThe document lists various Indian movie-themed video games created by different developers, including titles like 'Dhoom 3: The Game', 'PK: The Game', and games associated with popular films such as 'Bajrangi Bhaijaan' and 'Krrish 3'. It highlights the connection between Bollywood films and the gaming industry. Each game is linked to a specific movie or character, showcasing the integration of cinema and interactive entertainment.
Sql rally 2013 columnstore indexesДенис РезникSQL Server 2012 introduced columnstore indexes which provide significant performance improvements for data warehouse and analytics queries against large datasets. Columnstore indexes store data by column rather than by row, allowing queries to access only the relevant columns needed. This results in lower I/O and higher data compression compared to row storage. Columnstore indexes also use a new batch processing execution mode which can further improve query performance by processing many rows at once in memory rather than row-by-row. Columnstore indexes require the table to be read-only but provide an easy way to boost query performance for analytics workloads by 10-100x without needing separate data marts or cubes.
Column store indexes and batch processing mode (nx power lite)Chris AdkinThis document discusses SQL Server performance tuning with a focus on leveraging CPU caches through column store compression. It explains how column store compression can bridge the performance gap between IO subsystems and modern processors by breaking data through levels of compression to pipeline batches into CPU caches. Examples are provided showing significant performance improvements from column store compression and clustering over row-based storage and no compression.
3 indexesRam KedemThe document discusses indexes in SQL Server. It describes internal and external fragmentation that can occur in indexes. Internal fragmentation is unused space between records within a page, while external fragmentation is when page extents are not stored contiguously on disk. It provides examples of identifying fragmentation using system views and the dm_db_index_physical_stats dynamic management function. It also covers best practices for index types, such as numeric and date fields making good candidates while character fields are less efficient. Composite indexes, fill factor, and rebuilding vs. reorganizing indexes are also discussed.
Columnstore indexes in sql server 2014Antonios ChatzipavlisThis document provides information about an upcoming presentation on Columnstore Indexes in SQL Server 2014. It notes that the presentation will be recorded so that those who could not attend live can view it later. It requests that anyone with issues about being recorded should leave immediately, and remaining will be taken as consent to the recording. It also states the presentation will be free and will begin in 1 minute.
Intro to column storesJustin SwanhartThe document presents an introduction to column stores, contrasting them with row stores, and emphasizes their advantages in handling large datasets for analytical workloads. It discusses the inherent differences in data storage, retrieval efficiencies, and compression benefits of column stores, as well as some downsides, such as the expense of updates and potential inefficiencies when accessing all columns. Various column store implementations are compared, highlighting performance metrics and indexes suitable for different data handling scenarios.
SQL 2016 Mejoras en InMemory OLTP y Column Store IndexEduardo CastroEl documento detalla las innovaciones de SQL Server 2016, centrado en índices de columna y tablas en memoria, destacando su alta compresión y rendimiento en análisis en tiempo real. Se explican mejoras en la seguridad, escalabilidad y la capacidad de integrar soluciones híbridas con Azure. Además, se enfatiza la importancia de elegir el tipo de índice adecuado según las necesidades de las cargas de trabajo analíticas o transaccionales.
SQL Server 2016 noveltiesMSDEVMTLSQL Server 2016 introduces new capabilities to help improve performance, security, and analytics:
- Operational analytics allows running analytics queries concurrently with OLTP workloads using the same schema. This provides minimal impact on OLTP and best performance.
- In-Memory OLTP enhancements include greater Transact-SQL coverage, improved scaling, and tooling improvements.
- The new Query Store feature acts as a "flight data recorder" for databases, enabling quick performance issue identification and resolution.
The Top Skills That Can Get You Hired in 2017LinkedInThe document lists the top skills that can help job seekers get hired, based on LinkedIn data for 2016 across various countries. Key skills include statistical analysis, web development, network security, and mobile development, with variations depending on the country. This highlights the evolving job market and the importance of specific technical expertise in different regions.
소스트리(SourceTree)로 배우는 Git 사용법주형 고Source Tree로 버전 관리하는 법
- Git이 필요한 이유
- Stage(=Index에 기록)하기
- Commit하기
- Remote 추가하기
- Origin Remote로 GitHub 사용
- Push하기
- Clone하기
- Reset (Soft, Hard, Mixed)
- Revert
- Checkout, Detached HEAD
- 이전 Commit 수정하기
- Pull / Fetch&Merge하기
- Branch 만들기
- Fast Forward Merge하기
- 3-Way Merge하기
- 3-Way Merge에서 발생할 수 있는 Conflict 해결하기
- Visual Studio로 Conflict 해결하는 법
- Stash로 다양한 문제 해결해보기
- 오래된 저장소에서 Pull하기
- 다른 브랜치로 Commit 옮기기
- .gitignore 파일 설정하기
3 indexesRam KedemThe document discusses indexes in SQL Server. It describes internal and external fragmentation that can occur in indexes. Internal fragmentation is unused space between records within a page, while external fragmentation is when page extents are not stored contiguously on disk. It provides examples of identifying fragmentation using system views and the dm_db_index_physical_stats dynamic management function. It also covers best practices for index types, such as numeric and date fields making good candidates while character fields are less efficient. Composite indexes, fill factor, and rebuilding vs. reorganizing indexes are also discussed.
Columnstore indexes in sql server 2014Antonios ChatzipavlisThis document provides information about an upcoming presentation on Columnstore Indexes in SQL Server 2014. It notes that the presentation will be recorded so that those who could not attend live can view it later. It requests that anyone with issues about being recorded should leave immediately, and remaining will be taken as consent to the recording. It also states the presentation will be free and will begin in 1 minute.
Intro to column storesJustin SwanhartThe document presents an introduction to column stores, contrasting them with row stores, and emphasizes their advantages in handling large datasets for analytical workloads. It discusses the inherent differences in data storage, retrieval efficiencies, and compression benefits of column stores, as well as some downsides, such as the expense of updates and potential inefficiencies when accessing all columns. Various column store implementations are compared, highlighting performance metrics and indexes suitable for different data handling scenarios.
SQL 2016 Mejoras en InMemory OLTP y Column Store IndexEduardo CastroEl documento detalla las innovaciones de SQL Server 2016, centrado en índices de columna y tablas en memoria, destacando su alta compresión y rendimiento en análisis en tiempo real. Se explican mejoras en la seguridad, escalabilidad y la capacidad de integrar soluciones híbridas con Azure. Además, se enfatiza la importancia de elegir el tipo de índice adecuado según las necesidades de las cargas de trabajo analíticas o transaccionales.
SQL Server 2016 noveltiesMSDEVMTLSQL Server 2016 introduces new capabilities to help improve performance, security, and analytics:
- Operational analytics allows running analytics queries concurrently with OLTP workloads using the same schema. This provides minimal impact on OLTP and best performance.
- In-Memory OLTP enhancements include greater Transact-SQL coverage, improved scaling, and tooling improvements.
- The new Query Store feature acts as a "flight data recorder" for databases, enabling quick performance issue identification and resolution.
The Top Skills That Can Get You Hired in 2017LinkedInThe document lists the top skills that can help job seekers get hired, based on LinkedIn data for 2016 across various countries. Key skills include statistical analysis, web development, network security, and mobile development, with variations depending on the country. This highlights the evolving job market and the importance of specific technical expertise in different regions.
소스트리(SourceTree)로 배우는 Git 사용법주형 고Source Tree로 버전 관리하는 법
- Git이 필요한 이유
- Stage(=Index에 기록)하기
- Commit하기
- Remote 추가하기
- Origin Remote로 GitHub 사용
- Push하기
- Clone하기
- Reset (Soft, Hard, Mixed)
- Revert
- Checkout, Detached HEAD
- 이전 Commit 수정하기
- Pull / Fetch&Merge하기
- Branch 만들기
- Fast Forward Merge하기
- 3-Way Merge하기
- 3-Way Merge에서 발생할 수 있는 Conflict 해결하기
- Visual Studio로 Conflict 해결하는 법
- Stash로 다양한 문제 해결해보기
- 오래된 저장소에서 Pull하기
- 다른 브랜치로 Commit 옮기기
- .gitignore 파일 설정하기
[17.02.09] Github introduction (Korean Version)Ildoo KimGit 혹은 소스코드 형상관리를 아예 모르는 사람을 대상으로 작성한 Starter Guide입니다. 팀에 새로운 사람이 Join하는 등의 경우에 세미나 자료로 활용합니다.
형상관리/git 개념과 command line 혹은 source tree를 활용한 기본적인 사용 방법에 대해 소개합니다.
<팀을>이라는 책을 많이 참고하였습니다.
54. .
./.git
./.git/branches
./.git/config
./.git/description
./.git/HEAD
./.git/info
./.git/info/exclude
./.git/objects
./.git/objects/info
./.git/objects/pack
./.git/refs
./.git/refs/heads
./.git/refs/tags
앞서 Javascript 변수로 설명한
것들이 파일로 존재한다!
55. git init 명령직후에는 master 파일 내
용에 아무것도 없다
$ cat ./git/HEAD
ref: refs/heads/master
!
$ cat .git/refs/heads/master
cat: .git/refs/heads/master: No such file or directory
!
$ git branch
!
$
!
브랜치 역시 없는 상태
56. 간단히 README 파일을 생성한다
$ echo ‘just created’ README
!
$ ls -la
total 0
drwxr-xr-x 4 andrwj staff 136 11 25 00:18 .
drwxr-xr-x 3 andrwj staff 102 11 25 00:14 ..
drwxr-xr-x 14 andrwj staff 476 11 26 17:21 .git
-rw-r--r-- 1 andrwj staff 0 11 25 00:16 README
!
$ cat README
just created
!
$
현재 폴더에는 READ와
.git 폴더 뿐이다
58. $ cat .git/HEAD
!
ref: refs/heads/master
!!
그러나 여전히 master 파일의 내용은 비어있다
$ cat .git/refs/heads/master
cat: .git/refs/heads/master: No such file or directory
!!!
$ cat .git/object/4e/8238248ad38d598515adb865b818ec9381f967
!
x??Q
B!???????
??-?ied?]??
?;03K??
@???9Cd?9%t?I???Ή?(J+B?%e4?=n???
??L?s?^k(?????!???zkͤs3?߂????????/?
생성된 긴 이름의 파일을 출력해보니
TEXT 포맷의 파일이 아님을 알수있다
59. git blob format
헤더 정보를 포함하여 zlib로 압축되어 저장된다
헤더 형식: “blob 원본파일크기 null”
60. blob format
$ cd .git/object/4e/
$ python
fd = open(“8238248ad38d598515adb865b818ec9381f967”)
line = fd.read()
import zlib
zlib.decompress(line)
‘blob 13x00just createdn’
객체 종류는
‘blob’ 원본 크기는 13 바이트
null 바이트
원본 내용
61. git hash-object README
$ git hash-object README
4e8238248ad38d598515adb865b818ec9381f967
!
$ git cat-file -p 4e8238
just created
파일이름으로 해쉬명을 알 수 있다
파일이름 몇글자로
내용을 출력할 수 있다
62. why hash ?
내용에 따라 중복된 이름이 나올 가능성이 극히 드물다
육안으로 분별하기 힘든 차이도 쉽게 검출 가능하다
번호로된 파일 이름보다 관리 하기 쉽다(?)
파일명이 변경되어도 내용이 같으면 동일한 것으로
인식한다.
63. README
!
‘just created’
README
!
‘just created ‘
$ cat README
!
‘just created’
!!
끝부분 공백도 명확히 알 수 있다
$ git hash-object README
!
ec53c2432a2e9c2fadaa9d5982bd3cf31f9b38d2
!
$ cat README
!
‘just created ’
!!
$ git hash-object README
!
a6014d70c71eab934f3ac1248f8bad19ad3d451c
!
68. var blob = “헤더+내용이 zlib 로 압축된 문자열”;
!
var Tree = [
blob,
Tree,
];
!
var Commit = {
Javascript로 표현 ...
parent: { },
tree: [ ],
author: “string”,
date: “2011/11/30”
};
!
var Tag = “커밋을 가리키는 문자열”
69. blob object
Blob
header + content
!
zlib로 압축되어 있다
!
.git/objects/ 아래 있다
70. tree object
Tree
blob + 다른 tree 객체
!
‘폴더’와 같은 개념
!
.git/objects/ 아래 있다
71. commit object
Commit
blobs + trees + author
+ date + message
!
.git/objects/ 아래 있다
72. tag object
Tag
pointer to commit object
!
.git/refs/tags/ 아래있다
73. B
BB
T
TBT T
TBT T
prev
author
date
message
BTT TBT
Tag
BBB
prev
author
date
message
T
TBT T
TBT T
TBT
BBB
prev
author
date
message
T
TBT T
TBT T
TBT
Tag
BB
BT HEAD
master
예를 들자면...
74. 중간 정리
파일은 blob 포맷으로 저장된다.
폴더는 tree 객체로, 파일은 blob 객체로 표현된다.
commit, tag 역시 객체로 취급되어 파일형태로 저장된다.
모든 파일은 SHA 방식의 해쉬로 표현된다.
Git의 branch와 commit 은 pointer 이다.
75. three spaces
- Working area
!
- Staging or Index
!
- Local Repository
79. Repo
!R
Working Staging
EADME
$ cat ‘just created’ README
과정1 /11 - 처음으로 커밋할 파일을 생성
80. Repo
!R
Working Staging
EADME
$ cat README
just created
과정2 /11 - 파일 내용 보기
81. !
Repo
!R
Working
EADME
!R
Staging
EADME
$ git add README
스과테정이3 징/1 영1역 -에 스 파테일이 징정 보영 역기에록
파일 정보 기록
‘README’ 파일은 blob 형식으로 변환되어
.git/object/ 아래에 저장됨
82. !
Repo
!R
Working
EADME
!R
Staging
EADME
$ git ls-files -s
100644 4e8238248ad38d598515adb865b818ec9381f967 0 README
!
과정4 /11 - 스테이징 영역의 파일 정보 열람
(.git/index 파일 내용을 참조)
83. !
Repo
!R
Working
EADME
!R
Staging
EADME
$ ls -la .git/object/4e
drwxr-xr-x 3 andrwj staff 102 11 26 17:37 .
drwxr-xr-x 7 andrwj staff 238 11 26 18:06 ..
-r--r--r-- 1 andrwj staff 29 11 26 17:37 8238248ad38d598515adb865b818ec9381f967
과정5 /11 - ‘commit’ 단계에서 파일이 저장되는 것이 아니라,
‘add’ 단계에서 이미 저장되어 있는 것이
subversion 과 다른점!
84. !
Repo
!R
Working
EADME
!R
Staging
EADME
$ cat .git/index
??~?){???e?쓁?gREADME'mh?$
과정6 /11 - .git/index 파일은 TEXT 형식의 파일이 아
님.
85. !
!
Repo
!R
Working
EADME
!R
Staging
EADME
$ git commit -m ‘first commit’
[master (root-commit) b3d38eb] first commit
1 files changed, 1 insertions(+), 0 deletions(-)
create mode 100644 README
!R
C1: b3d38eb
EADME
!
과정7 /11 - 이미 README 저장되어 있으므로
‘commit’ 단계에선 스테이징 영역의 리스트를 참조
하여 commit object를 만든다
88. !
!
Repo
!R
Working
EADME
!R
Staging
EADME
!R
C1: b3d38eb
EADME
!
$ git cat-file -p b3d38eb6591fc4737509a00471e9a64ba4f79c5c
tree b529edd1315d7d85716378eb7829ba0772542851
author AJ andrwj@gmail.com 1322298365 +0900
committer AJ andrwj@gmail.com 1322298365 +0900
과정10 /11 - 커밋객체(파일)의 내용을 출력해보면
tree 객체와 커밋한 사용자와 날짜 및
커밋 메세지를 볼 수 있다.
89. !
!
Repo
!R
Working
EADME
!R
Staging
EADME
!R
C1: b3d38eb
EADME
!
$ file . -name ‘*d38eb6591fc4737509a00471e9a64ba4f79c5c’
./.git/objects/b3/d38eb6591fc4737509a00471e9a64ba4f79c5c
과정11 /11 - 커밋객체(파일) 역시 .git/objects/ 폴더 아래에 있다.