PostgreSQL is an object-relational database (ORDBMS) that was introduced into
the database community and has been avidly used for a variety of information
extraction use cases. It is also known to be an advanced SQL-compliant open
source Object RDBMS. However, users have not yet resolved to PostgreSQL due to
the fact that it is still under the layers and the complexity of its persistent
textual environment for an amateur user. Hence, there is a dire need to provide
an easy environment for users to comprehend the procedure and standards with
which databases are created, tables and the relationships among them,
manipulating queries and their flow based on conditions in PostgreSQL. As such,
this project identifies the dominant features offered by Postgresql, analyzes
the constraints that exist in the database user community in migrating to
PostgreSQL and based on the scope and constraints identified, develop a system
that will serve as a query generation platform as well as a learning tool that
will provide an interactive environment to cognitively learn PostgreSQL query
building. This is achieved using a visual editor incorporating a textual editor
for a well-versed user. By providing visually-draggable query components to
work with, this research aims to offer a cognitive, visual and tactile
environment where users can interactively learn PostgreSQL query generation.
Sri Lanka Institute of Information Technology, Sri Lanka
スリランカ情報技術研究所(sri lanka institute of information technology)
0.60
PostgreSQL is an object-relational database (ORDBMS) that was introduced into the database community and has been avidly used for a variety of information extraction use cases.
It is also known to be an advanced SQL-compliant open source Object RDBMS.
高度なSQL準拠のオープンソースObject RDBMSとしても知られている。
0.74
However, users have not yet resolved to PostgreSQL due to the fact that it is still under the layers and the complexity of its persistent textual environment for an amateur user.Hence, there is a dire need to provide an easy environment for users to comprehend the procedure and standards with which databases are created, tables and the relationships among them, manipulating queries and their flow based on conditions in Postgresql.
As such, this project identifies the dominant features offered by Postgresql, analyzes the constraints that exist in the database user community in migrating to Postgresql and based on the scope and constraints identified, develop a system that will serve as a query generation platform as well as a learning tool that will provide an interactive environment to cognitively learn PostgreSQL query building.
This is achieved using a visual editor incorporating a textual editor for a well-versed user.
これは、テキストエディタを組み込んだビジュアルエディタを使って、会話の行き届いたユーザに提供する。
0.69
By providing visually-draggable query components to work with, this research aims to offer a cognitive, visual and tactile environment where users can interactively learn PostgreSQL query generation.
I. INTRODUCTION POSTGRESQL, also simply referred to as Postgres, is an
私は... 導入 postgresqlは単にpostgresとも呼ばれます。
0.46
erudite open-source Object- Relational DBMS that serves as a subsidiary to practically all SQL constructs, including sub selects, transactions, and user-defined types.
As stated throughout the project, the lack of awareness of Postgresql and its attached beneficiary functionalities over any other existent systems, stated the dire need to elucidate the entire workings of Postgresql.
And hence an analysis on the reasons as to why Postgresql suffers a low prominence in utilization, the constraints that keep Postgresql from being renowned and a study on existing contender systems was carried out in order to build a system that triggers learnability within a development environment for Postgresql database creation and table querying functionalities.
A. Postgresql’s support for languages and platforms
A. Postgresqlが言語とプラットフォームをサポート
0.81
PostgreSQL is compatible with many of the dominant Operating Systems such as Windows, Linux, UNIX (AIX, BSD, HP-UX, SGI IRIX, Mac OS X, Solaris, and Tru64).
PostgreSQLは、Windows、Linux、UNIX(AIX、BSD、HP-UX、SGI IRIX、Mac OS X、Solaris、Tru64)などの主要なオペレーティングシステムと互換性がある。 訳抜け防止モード: PostgreSQLはWindowsのような支配的なオペレーティングシステムの多くと互換性がある。 Linux, UNIX (AIX, BSD, HP - UX, SGI IRIX, Mac OS X, Solaris, Tru64 )。
0.89
It 1 provides avid support to various forms of data that include Text, Image, Audio and Video.
The parameters that could be passed in specifying the database are the database name, description and options such as command-line arguments which it accepts.
PostgreSQL statement CREATE SCHEMA creates a schema [4].
PostgreSQL文 CREATE SCHEMAはスキーマを生成する[4]。
0.78
CREATE SCHEMA <name>;
クリートSCHEMA<name>;
0.55
A table in the schema can be created using;
スキーマ内のテーブルを作成できる。
0.50
CREATE TABLE <myschema.mytable> (...);
CREATE TABLE <myschema.mytable> (...)
0.42
C. Postgresql Operators
C. Postgresql オペレータ
0.90
The definition of an operator explains it as an earmarked keyword or a character that bears a prime functionality in a Postgresql statement WHERE clause to accomplish the intended filter, comparison, arithmetic or related operations [5].
Operators also function as binding points that collaborate omni various statements endorsed on a query and serve the accumulated conditions’ results via execution.
D. Constraints and the various levels at which they can be enforced
d. 施行可能な制約及び各種レベル
0.54
Constraints can be mentioned as the rubrics imposed on data columns of the database table.
制約は、データベーステーブルのデータ列に課されるルーリックとして言及することができる。
0.70
Constraints bar the entry of inacceptable data being passed into the database.
制約は、データベースに渡される許容できないデータの入力を禁止する。
0.69
This confirms the precision and dependability of the data in the database.
これはデータベース内のデータの正確性と信頼性を確認する。
0.80
Constraints can be formulated to adhere to the column level or table level.
制約はカラムレベルやテーブルレベルに準拠するように定式化することができる。
0.70
Column level constraints are functional only on one column while table level constraints are functional to the unabridged table.
列レベルの制約は1つの列でのみ機能し、テーブルレベルの制約は非ブリッジテーブルで機能する。
0.71
The process of outlining a data type for a column can be considered as a constraint in itself.
カラムのデータ型を概説するプロセスは、それ自体が制約と見なすことができる。
0.69
Since data types automatically validate the values that are allowed to be stored in columns while inserting into the database, without the interference or specification from a user or developer, declaration of column data types are readily deemed as the easiest and lowest level of constraint declaration [6].
For example, a column declared with the data type STRING constrains the column to permit the entry of solely string values.
例えば、データ型STRINGで宣言された列は、列を制約し、単に文字列値の入力を許可する。
0.70
Some of the very notably available and utilized constraints within Postgresql’s operation are tabularized below.
Postgresqlの操作で非常に顕著に利用でき、利用可能な制約のいくつかは以下に表されている。
0.61
TABLE I. Constraint Description
テーブルI。 制約 解説
0.59
NOT NULL UNIQUE
null ではない ユニキュー
0.50
FOREIGN Key CHECK EXCLUSION
外国キー チェック 排ガス
0.46
are via this the
は 経由 これ その...
0.55
that column constraint constraint
あれ コラム 制約 制約
0.66
Guarantees column doesn’t permit the entry of null values Guarantees that all values within a distinct and different from one another the extends This specified the to columns referenced column in another table Conditions on columns can be type specified of constraint.
specified constraint will be validated for all values that are stored in the column This restriction certifies that if any two rows are likened on the indicated column/ columns or expression/expressio ns using the stated operator/operators, not all of these evaluations are bound to return TRUE
It This proposed system is intended to induce the utilization and elucidate the importance and advantages of PostgreSQL, which is an object-relational database (ORDBMS) that was recently introduced into the database community and has been proven to be superior to the well-renown MySQL in many ways.
But, users have not yet resolved to Postgresql due to the facts that it is still under the layers and the complexity of its persistent textual environment for an introductory user.
Simply stating this, there is a dire need to elucidate an easy way of making the users comprehend the procedure and standards with which databases are created, tables and the relationships among them, manipulating queries and their flow based on conditions in Postgresql to help the community resolve to Postgresql at an augmented rate.
Hence, this project tends to identify the dominant features provided by Postgresql over MySQL, analyze the constraints that exist in the database user community in moving towards the utilization of Postgresql and based on the scope and constraints identified, develop a system that will serve as a designing platform as well as a learning tool that will provide an interactive method of learning via a visual editor mode and incorporate a textual editor for a well-versed user.
By providing a visually draggable and manipulative environment to work with Postgresql databases and queries, it is expected to highlight the advanced features displayed by Postgresql over any other existent systems in order to grasp and disseminate the importance and simplicity offered by this language to a hesitant user.
A. Concerns that led to the lack of potential users
A.潜在的なユーザ不足の原因となる懸念
0.80
The reason to direct major focus towards Postgresql is the fact that in spite of its numerous advantages over any current SQL compliant DBMS, Postgresql is not a database server in vogue.
As a questionable research topic on why such hesitance still exists, the following concerns were identified.
なぜそのようなためらうのかという疑問が残る研究テーマとして、以下の懸念点があげられる。
0.56
- The hassle of learning new standards and processes over well-known database management systems such as MySQL.
-MySQLのようなよく知られたデータベース管理システムで新しい標準とプロセスを学ぶのが面倒です。
0.75
- Provided the advanced features of this tool, there are deficiencies in rapports of popularity, despite the extreme implementations.
-このツールの高度な機能により、極端な実装にもかかわらず、人気度が低下する。
0.62
This affects the level of ease with which support is made available
これはサポートが利用可能になる際の容易さに影響を及ぼす
0.77
Misconceptions about the platform that permits complex custom solutions- Postgresql is well adopted to incorporate complex custom solutions since it is extensible.
Hence, based on the concerns identified, it was conclusive that learnability and comprehensibility were two major attributes that affected the user migration from other platforms to Postgresql.
So this research based system being developed tends to identify the ways and features that a development platform for Postgresql needs and build a development environment that will serve both the amateur users as well as the well-versed users via interactive modes of database creation and manipulation.
to have B. Perspective of conjuring a feasible product
to have ～ b. 実現可能な製品の構築の展望
0.59
Though there are IDEs to work on PostgreSQL databases management, these existing workspaces do not focus on inducing learnability of PostgreSQL via interactive operations.
Learnability of the system can be measured using the
システムの学習能力は、それを使って測定できる。
0.61
following ways. - Effectiveness: Number of functions that could be learnt from working on the system.
次の方法で -有効性: システムの開発から学ぶことのできる関数の数。
0.74
- Efficiency: The time taken to learn a new function via interacting with the Application.
- 効率性: アプリケーションとのインタラクションを通じて新しい機能を学ぶのに要する時間。
0.90
- Satisfaction: The perceived value of the user associated with their investment (Time, Effort and Cost) in learning how to use a particular functionality on the system.
- Errors: The number of errors that are possible to be met when working on the Application and the time or methods to recover from the incurred erroneous state.
Based on these measurable and assumable attributes, the UI design for a Visual Editor that encapsulates learnability as a key component had to be analyzed.
To do so, the Info-graphic of Interaction Principles [12] by David Hogue was evaluated on a research basis.
そのためにDavid Hogue氏のInfo-graphic of Interaction Principles[12]を研究ベースとして評価した。
0.82
According to David Hogue’s core principle of Interaction Design, Comprehensibility is coherent with learnability as shown in Fig 1.
david hogue氏のインタラクション設計のコア原則(source)によると、理解可能性は図1に示すように、学習可能性と一貫性がある。
0.51
Fig. 1 V. TARGET MODEL FOR POSTGRESQL LEARNABILITY
第1図 v.postgresql learnabilityのターゲットモデル
0.60
A. System components
A.システムコンポーネント
0.80
Bearing in mind all the pre-calculated and evaluated features, constraints and feasible factors, a system with the following components can be considered as a viable solution to the concern at hand.
A personalized user dashboard for each registered user creates an illusion separating multiple logged in user sessions from one another providing privacy and manageability of one’s own databases and query projects.
There are basically two user classes focused within the
基本的に2つのユーザークラスがある。
0.72
1) Novice users These users are those who have a certain level of database knowledge and know to work their way within a database environment in general.
But the 4 reason to accommodate these users within the system’s context is to provide a broader scope and capture more target audience instead of extending the usability of the system to mere amateur users.
LEARNING The Visual Editor is predominantly intended towards the provision of learnability of Postgresql concepts and techniques for amateur users as considered within this context.
- Database and Table creation - Query Builder for Table Data Retrieval
-データベースとテーブル作成-テーブルデータ検索のためのクエリビルダー
0.89
Each of these are elucidated in detail here.
いずれも詳細はこちらを参照のこと。
0.63
A. Database and table creation within the Visual Editor
A. Visual Editor 内のデータベースとテーブル作成
0.82
The various functionalities that are broken down within this major context of creating databases and tables, consider the implementation of each of these features.
1) Effectiveness a) Creating database or schema object
1)有効性 a)データベースまたはスキーマオブジェクトの作成
0.84
Most of the web based visual editors currently provide less number of options while creating users or databases or schema objects like tables, novice users are unable to learn available options for databases or schema objects in Postgresql [13].
Users have to navigate pages to identify available options.
ユーザーは利用可能なオプションを特定するためにページをナビゲートする必要がある。
0.49
So the percentage of users who manage to learn the criterion is less.
ですから、この基準を学べるユーザの割合は、少ないのです。
0.67
Insufficient in learning a single task or function.
1つのタスクや機能を学ぶのに不十分です。
0.52
In our tool we have provided a single form with multiple options to create database or schema objects therefore beginners may feel convenient while using, they don’t need to access many pages.
For instance as shown in Fig 2, while creating a table with columns and when the user moves the cursor to that particular data type like double precision, serial our visual editor describes it.
In the user creation task of our product, the available components are user name and single or multiple user configuration selections like super user, created role, and password [15].
Make commands and menu options highly visible and easy to find.
コマンドとメニューオプションを高度に可視化し、見つけやすくする。
0.81
For example near the database object that they impact - a right click on that database or if they click on the dropdown icon displays a list of available operations like creating new table and view existing tables as shown in below Fig 4.
Prompting out successful or failure messages after object creation this feature may help users to find out whether their schema objects were created on their specific database.
As shown in Fig 3 if a user clicks on ‘+ New table’, it redirects to create a table page.
図3に示すように、ユーザが‘+ New table’をクリックすると、テーブルページを作成するようにリダイレクトされる。
0.86
After creating the table it shows a successful or failure message.
テーブルを作成すると、成功または失敗のメッセージが表示される。
0.71
According to time satisfaction, if they navigate the table list, users will be able to view existing tables of that database, add columns menu and table drop option.
Unique option is compatible with some index methods of tables like ‘btree’ index method supports unique option but ‘hash’ method does not have unique option.
For instance if a user starts typing database names in digits, we should provide an error message and give a solution to sort it out like giving a message to start with letters.
B. Query Builder for table data retrieval within the Visual Editor The query builder for Postgresql table queries is an interactive environment that consists of the following 3 elements.
B. Query Builder for table data retrieve in the Visual Editor Postgresql table queryは、以下の3つの要素からなる対話型環境である。
0.77
5
5
0.42
英語（論文から抽出）
日本語訳
スコア
- The Toolbox - The Canvas - Properties panel
-ツールボックス - Canvas - プロパティパネル
0.70
The Toolbox will be a host of the elements that represent the various clauses in the Postgresql query statements.
Users will be permitted to drag and drop the elements onto the canvas.
ユーザーはcanvasに要素をドラッグ&ドロップすることができる。
0.66
Preceding the drop of an element onto the canvas, that element will be cloned on the canvas so that the user can freely move and manipulate this element within the canvas.
The canvas will contain the elements’ movement so that the elements are not extendable out of that container.
キャンバスには要素の動きが含まれており、要素がそのコンテナから拡張されないようにします。
0.68
The properties panel is a dynamic property declaring window that is created and made visible only when the user chooses to set the properties of a particular element.
Based on the element chosen, the property attributes of the element will be gathered with regard to the connections that the element bears at the moment within the container and display the available and valid properties that could be assigned for that element.
The crucial features that were considered in formulating the features, design principles, location, minimization and visibility of the interface elements of the Query Builder Interface in order to facilitate learnability are stated here.
As suggested via Hogue’s core principles, there needs to be Evidence of action.
Hogueのコア原則によって提案されているように、行動のエビデンスが必要だ。
0.72
Learnability is provided through traceability of a certain action.
学習性は特定の行動のトレーサビリティを通じて提供される。
0.56
In touch screen functionalities, the previous actions are lost unless they are stored by coded means.
タッチスクリーン機能では、コード化された手段で保存されない限り、前のアクションは失われる。
0.64
Likewise, when an application’s intention is to provide a learning platform, the users’ previous actions need to be traceable to identify and correlate the tasks performed with the output rendered.
To solve this issue, the Visual editor will provide a “History” option where past actions or functions performed can be viewed by the user as part of the model and its connected network of elements that the query clauses.
- Provides alternatives Once the user completes a query creation, suggest a
-代替品 ユーザがクエリ生成を完了すると、提案します。
0.54
alternative query optimization patterns cost-effective design.
代替クエリ最適化パターン コスト効率の良い設計。
0.68
to enhance
to enhance
0.42
- Is attained at low cost
-低コストで達成される
0.90
The system will be implemented as a web application
システムはwebアプリケーションとして実装されます
0.87
incurring no additional software or hardware purchases.
追加のソフトウェアやハードウェアの購入は行いません
0.65
In balancing learning components with UI components, the proportion of UI features should maintain a minimalistic design without overwhelming the users’ cognitive load [18].
Upon the users’ will, advanced features of PostgreSQL can be accessed and utilized at no cost.
ユーザの意思により、PostgreSQLの高度な機能にアクセスして、無償で利用することができる。
0.70
A balance between learnability and UI component features needs to be optimized to provide an environment that facilitates teaching in subtlety without letting the user be disrupted as shown in Fig. 5.
Fig. 5 The following features will be implemented to make
第5図 以下の機能が実装される予定だ。
0.76
learning easy via the usage of the application.
アプリケーションの利用を通じて簡単に学習できる。
0.81
a) Scaffolding
scaffolding (複数形 scaffoldings)
0.16
This is the process where the application will direct an amateur user to gradually move into the difficulty level via properly guided instructions and tailored clause flows.
Based on this revelation by Barry Schwartz, more options does not directly indicate user freedom.
バリー・シュワルツによるこの暴露に基づき、より多くのオプションはユーザー自由を直接示さない。
0.66
Instead it toils with happiness increasing anxiety.
その代わり、不安を増す幸せで苦しむ。
0.71
Applying this concept to our Visual Editor, providing the basic and mandatory elements at first sight while hiding the advanced limited operational environment.
d) Mental Models This is what the user expects the system to perform.
d)精神モデル これはユーザがシステムが実行すると期待することです。
0.79
There are 3 ways to bind the users’ mental model with the actual system.
ユーザのメンタルモデルを実際のシステムにバインドする方法は3つあります。
0.73
6
6
0.43
英語（論文から抽出）
日本語訳
スコア
system to conform to
システム conform + -ly
0.36
users’ TABLE II.
ユーザ テレビII。
0.44
(cid:0) Design UI to better communicate the system’s nature
(cid:0)システムの性質をより良く伝えるためのui設計
0.77
in order to correct the users’ mental model.
ユーザのメンタルモデルを修正するために。
0.55
(cid:0) Educate users
(cid:0)教育 ユーザ
0.58
to adapt to the
へ 適応 へ その...
0.52
application (cid:0) Redesign
応用 (cid:0)再設計
0.50
the understanding. environment. Out of the afore-mentioned, option b will be followed by conducting onsite observation, discussion and interviews with potential user classes to draw up an idea about the users’ mental model.
Based on the conjured mental model, the UI will be designed to align with the users’ expectations.
判断されたメンタルモデルに基づいて、UIはユーザの期待に合致するように設計される。
0.72
When option b fails and the user is left with no clue of the next step to proceed onto, the user can choose to be educated via a brief tutorial that elucidates the system’s functionalities from scratch.
e) Intrinsic Complexity This is about reducing the user’s extraneous cognitive load [12] by making each element’s functionality more obvious to the users to avoid making them remember it.
But at the same time these experts won’t be hurt by design guidelines that apply to the novice users.
しかし同時に、これらの専門家は初心者ユーザーに適用されるデザインガイドラインに傷を負わないだろう。
0.83
Though this is the case, sometimes rules for novices can decrease the learning outcomes for experts by slowing them down.
このような場合もありますが、初心者のルールは、専門家の学習結果を遅くすることで減少させます。
0.61
So since our target group comprises both the novice and expert users the instructions and guidelines will be tailored to provide enough information for a novice user to work on the system and simultaneously not hinder an expert user’s work effort/speed.
But methods of recovery and guidance will be available upon the user’s breaking point.
しかし、リカバリとガイダンスの方法は、ユーザのブレークポイントで利用できるようになる。
0.68
Since the other existing products with relation to PostgreSQL do not focus on providing a learning platform for users as well as an operational environment for experts, the system under development in our context, based on all of these conclusive learnability features, the Visual Editor’s UI design and component features have been drawn for implementation.
1) Mapping the elements to the query clause representation
1)要素をクエリ句表現にマッピングする
0.73
The query builder’s intention is to create a visually comprehensible model that educates the user about the query flow and execution by simply being able to display it obviously.
Hence, the following elements were chosen to represent the query clauses for easy comprehensibility.
そのため、簡単な理解のために以下の要素が選択された。
0.66
Likewise, connectivity between dropped elements, the properties panel elements and the dynamicity in the overall flow and interface components of the visual editor are all aligned towards the provision of an exclusive query builder that not only functions as a development environment, but also a learning environment.
PROPOSED SYSTEM The Text editor is a mere execution text pad that paves way for the Postgresql database user to type in text, execute and run it in order to retrieve intended results or queries on the
In there it is important to understand what the main objective of using the software is.
そこでは、ソフトウェアを使う主な目的が何であるかを理解することが重要です。
0.81
If the Software system only addresses the stakeholders main verbally communicated requirements which are considered as functional requirements it will not be considered as a customer valued software system.
Software system quality represents one or more structural aspects, which illustrates how the architecture addresses the concerns such as requirements, objectives, intention of stakeholders for the architecture design [20].
Usability of a software system is one of the main quality attributes.
ソフトウェアシステムのユーザビリティは、主な品質特性の1つです。
0.77
It focuses on the ability of a system to perform well.
システムは、うまく機能する能力に重点を置いている。
0.78
For a given task how the software system performs.
特定のタスクに対して、ソフトウェアシステムがどのように振る舞うか。
0.56
How the system performance can be improved.
システムパフォーマンスをどのように改善するか。
0.82
Usability of a system addresses a user who is a novice user.
システムのユーザビリティは、初心者ユーザであるユーザに対処する。
0.82
Assuming that the user does not have experience with computers, Experience with interface is none, domain knowledge is none and experience with similar type of software is none [21].
In Software Engineering usability is the degree to which a software can be used by specific consumers to archive and quantify objectives with effectiveness, efficiency and satisfaction in a quantified context of use.
And also these features will guide the user to learn the system within a short time.
さらにこれらの機能は,ユーザが短時間でシステムを学ぶためのガイドにもなる。
0.75
B. The Enhanced provident Environment within the Text Editor Enhancement of a user provided query is available through an optimization option that the text editor will provide.
B. テキストエディタ内の拡張提供環境 テキストエディタが提供する最適化オプションを通じて、ユーザが提供するクエリの強化を行うことができる。
0.88
The query optimization intends on suggesting alternatives to optimize the existing query that the user has typed.
This tool provides a way for users to get a clear idea about query optimization.
このツールは,クエリ最適化に関する明確なアイデアをユーザに提供するものだ。
0.82
Users can get the query plan of executed Postgresql query.
実行中のPostgresqlクエリのクエリプランを取得することができる。
0.67
It contains query execution time, query planning time, query cost and other details.
クエリの実行時間、クエリ計画時間、クエリコストなどの詳細が含まれている。
0.65
Output displays in a user friendly way.
出力はユーザフレンドリーに表示されます。
0.75
Therefore it will increase the learnability and the usability of the tool.
これにより、ツールの学習可能性とユーザビリティが向上する。
0.71
This tool provides query optimization tips for each and every query.
このツールは、クエリごとにクエリ最適化ヒントを提供する。
0.67
It will help users to get an idea about whether the query is further optimizable or not.
クエリがさらに最適化可能かどうかについて、ユーザがアイデアを得るのに役立つだろう。
0.70
Users need to understand the query optimization tips and change their query accordingly and observe the execution time.
ユーザはクエリ最適化のヒントを理解し、クエリを適切に変更し、実行時間を監視する必要がある。
0.67
By comparing query plans users can decide which query is the best for the execution.
クエリプランを比較することで、どのクエリが実行に最適なのかを決定できる。
0.69
As this tool fulfills the ultimate goal of any database system is to allow efficient querying by minimizing response time of the queries through performance tuning.
Some techniques that were adhered in order to facilitate
固執する技法もいくつかありますが
0.57
query optimization are stated here below [32].
クエリの最適化は以下の通りです [32]。
0.71
a) Specific column name instead of * in SELECT Example: Writing the query as SELECT col_1, col_2, col_3, col_4 FROM table_name; Instead of: SELECT * FROM table_name;
a) 選択した例で * の代わりに特定のカラム名。 select col_1, col_2, col_3, col_4 を table_name から記述する。 訳抜け防止モード: a) SELECT Example : クエリをSELECT col_1として記述する col_2 , col_3 , col_4 from table_name ; instead of : SELECT * from table_name ;
0.90
b) Try to avoid HAVING Clause in Select statements
b)選択文にクロースを記載することを避けること
0.67
HAVING clause is used to filter the rows after all the rows are selected and is used like a filter.
すべての行が選択された後に、節をフィルタするために使用され、フィルタのように使用される。
0.66
Hence the HAVING clause should be avoided for any other purpose.
したがって、Hiding節は他の目的のために避けるべきである。
0.52
c) Avoid the use of DISTINCT clause where applicable
c) 適用可能なDISTINCT条項の使用を回避すること
0.82
DISTINCT clauses will result in performance degradation.
DISTINCT節は性能劣化をもたらす。
0.61
So this clause should be used only when it is necessary or unavoidable.
したがって、この条項は必要か避けられない場合にのみ使用されるべきである。
0.60
d) Alternatives of COUNT (*) for returning total tables row count
d)全表行数を返すためのCOUNT(*)の代替品
0.80
If the table's row count is required to be returned, alternative ways instead of the SELECT COUNT (*) statements need to be used.
The UNION ALL statement is faster than UNION, because
UNION ALL文はUNIONよりも高速である。
0.78
UNION ALL statement does not consider duplicates.
UNION ALL文は重複を考慮しない。
0.66
CONCLUSION Postgresql is an Object Relational Database Management System that has received diminished reputation and utilization among the database community over the years.
Hence, in order to create more awareness and migration towards Postgresql, the current issues and concerns that relate to this low level of Postgresql users had to be identified.
As such, the current features provided by Postgresql, the dominant features that Postgresql possesses over its competitors, the constraints that it suffers as a product in the market were analyzed and based on that a viable system has been proposed and developed.
This system will function as a development environment for Postgresql databases and queries.
このシステムはPostgresqlデータベースとクエリの開発環境として機能する。
0.85
But due to the reasons identified via the factors under concern, the lack of Postgresql knowledge among users dictated the system under development to bear learnability as a mandated feature in its environment.
Hence, the system has been developed by researching the provision of learnability through visual manipulations and interactivity via a Visual Editor and for the more advanced users, a Text editor with query optimization and execution facilitations.
This paper tends to revolve around the simultaneous provision of learnability and a development environment to both novice and professional users through Visual Elements and interactive dynamicity.
https://www.postgres ql.org/docs/9.5/stat ic/sql-createuser.ht ml [16] 27, https://www.postgres ql.org/docs/9.1/stat ic/indexes-types.htm l [17] Nielsen Norman Group.
https://www.postgres ql.org/docs/9.5/stat ic/sql-createuser.ht ml [16] 27 https://www.postgres ql.org/docs/9.1/stat ic/indexes-types.htm l [17] Nielsen Norman Group
0.20
https://www.nngroup. com/articles/usabili ty-101-introduction- to-usability/ [18] Van Gerven, Pascal W. M. (2003/03/01).
https://www.nngroup. com/articles/usabili ty-101-introduction- to-usability/ [18] Van Gerven, Pascal W. M. (2003/03/01)。
0.22
Cognitive Load Measurement as a Means to Advance Cognitive Load Theory.
認知負荷理論を前進させる手段としての認知負荷測定。
0.64
Educational Psychologist, 38, 63-71.
教育心理学38,63-71。
0.76
doi: 10.1207/S15326985EP3 801_8 [19] Schwartz, B. (2004, January).
doi: 10.1207/s15326985ep3 801_8 [19] schwartz, b. (2004年1月)
0.62
The paradox of choice: Why more is less.
選択のパラドックス:なぜ多くは少ないのか。
0.61
New York: Ecco.
ニューヨーク州:ecco。
0.73
[20] Dr.A.
20] dr. a.
0.42
Chandrasekar, Mrs Sudharajesh, Mr P Rajesh.
チャンドラセカールさん、スダラエシュさん、プ・ラエシュさん。
0.40
A Research Study on Software Quality attributes.
ソフトウェア品質特性の研究。
0.55
International Journal Of Scientific & Technology Research Volume4, Issue 1, January 2014 ISSN 2250-3153 [21] Tovis Grossman, George Fitmaurice, Ramtin Attar.
International Journal of Scientific & Technology Research Volume4, Issue 1 2014 ISSN 2250-3153 [21] Tovis Grossman, George Fitmaurice, Ramtin Attar 訳抜け防止モード: International Journal of Scientific & Technology Research Volume 4, Issue 1 2014年1月 ISSN 2250 - 3153 [21 ] Tovis Grossman ジョージ・フィッツモーリス(George Fitmaurice) - イギリスの俳優。
0.66
Autodesk Research.
autodesk research所属。
0.82
210 King St.East, Toronto,Ontario, Canada, M5A 1J7 [22] Lazar, J., Jones, A. and Shneiderman, B. (2006).
210 King St.East, Toronto, Ontario, Canada, M5A 1J7 [22] Lazar, J., Jones, A. and Shneiderman, B. (2006) 訳抜け防止モード: 210 カナダ・オンタリオ州トロントのセント・イースト国王 M5A 1J7 [ 22 ] Lazar, J., Jones, A。 とShneiderman, B. (2006)。
0.88
Workplace user frustration with computers: An exploratory investigation of the causes and severity.
コンピュータによる職場ユーザのフラストレーション:原因と重大性の探索的な調査。
0.77
Behaviour and Info. Technology.
行動と情報。 テクノロジー
0.53
25(3):239-251 [23] Howes, A. and Young, R. M. (1991).
25(3):239-251 [23] howes, a. and young, r. m. (1991)
0.45
Predicting the learnability of task-action mappings.
タスク・アクションマッピングの学習可能性の予測。
0.58
ACM CHI. 1204-1209.
ACM CHI。 1204-1209.
0.58
[24] Twidale, M. B. (2005).
[24] twidale, m. b. (2005)
0.35
Over the Shoulder Learning: Supporting Brief Informal Learning.
肩書き学習: 簡潔なインフォーマルな学習を支援する。
0.71
CSCW.14(6):505-547.
CSCW.14(6):505-547。
0.65
[25] Stickel, C., Fink, J. and Holzinger, A. (2007).
[25] Stickel, C., Fink, J. and Holzinger, A. (2007)。
0.44
Enhancing Universal Access–EEG Based Learnability Assessment.
ユニバーサルアクセス-EEGに基づく学習可能性評価の強化。
0.55
Lecture Notes in Comp.
Compの講義ノート
0.57
Sci. 813-822.
Sci 813-822.
0.30
[26] Haramundanis, K. (2001).
[26]Haramundanis, K. (2001)。
0.41
Learnability in information design.
情報設計における学習能力。
0.66
ACM SIGDOC.
ACM SIGDOC所属。
0.83
7-11. [27] Michelsen, C. D., Dominick, W. D. and Urban, J. E. (1980).
7-11. (27)Michelsen, C. D., Dominick, W. D. and Urban, J. E. (1980)
0.40
A methodology for the objective evaluation of the user/system interfaces ofthe MADAM system using software engineering principles.
ソフトウェア工学の原理を用いたMADAMシステムのユーザ/システムインタフェースの客観的評価手法
0.75
ACM Southeast Regional Conference.
ACM東南アジア地域会議。
0.74
103-109. [28] Nielsen, J. (1994).
103-109. [28]Nielsen, J. (1994)。
0.35
Usability Engineering.
ユーザビリティエンジニアリング。
0.61
Morgan Kaufmann.
モーガン・カウフマン。
0.50
[29] P.Jyotsnai, P.Sunil Kumar Reddy, P.Govindarajajulu, Dept of Computer science,S.V.Universi ty, Tirupat(2013) Effective Implementation Of Query Optimization Through Performance Tuning Tecniques On Web [30] Yannis E. Ioannidis,Query Optimization,Compute r Sciences Department,Universit y of Wisconsin,Madison, WI 53706 [31] Saurabh gupta,Gopal Singh Tandel,Umashankar Pandey, A Survey on Query Processing and Optimization in Relational Database Management System [32] Jean Habimana, Query Optimization Techniques - Tips For Writing Efficient And Faster SQL Queries,Internationa l Journal Of Scientific & Technology.
[29] P.Jyotsnai, P.Sunil Kumar Reddy, P.Govindarajajulu, Dept of Computer science,S.V.Universi ty, Tirupat(2013) Effective Implementation Of Query Optimization Through Performance Tuning Tecniques On Web [30] Yannis E. Ioannidis,Query Optimization,Compute r Sciences Department,Universit y of Wisconsin,Madison, WI 53706 [31] Saurabh gupta,Gopal Singh Tandel,Umashankar Pandey, A Survey on Query Processing and Optimization in Relational Database Management System [32] Jean Habimana, Query Optimization Techniques - Tips For Writing Efficient And Faster SQL Queries,Internationa l Journal Of Scientific & Technology. 訳抜け防止モード: P.Jyotsnai, P.Sunil Kumar Reddy, P.Govindarajajulu, Dept of Computer Science S.V.University, Tirupat(2013 ) Effective implementation of Query Optimization through Performance Tuning Tecniques on Web [30 ] Yannis E. Ioannidis, ウィスコンシン大学マディソン校コンピュータ科学科クエリ最適化 WI 53706 [31 ] Saurabh gupta, Gopal Singh Tandel, Umashankar Pandey リレーショナルデータベース管理システムにおけるクエリ処理と最適化に関する調査 [32] Jean Habimana, クエリ最適化テクニック - 効率的で高速なSQLクエリを書くためのヒント International Journal of Scientific & Technology(英語)