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How To Create a New User and Grant Permissions in MySQL. What the Red Means The lines that the user needs to enter or customize will be in red in this tutorial! The rest should mostly be copy-and-pastable. About MySQL MySQL is an open source database management software that helps users store, organize, and later retrieve data. How to Create a New User In Part 1 of the MySQL Tutorial, we did all of the editing in MySQL as the root user, with full access to all of the databases. Let’s start by making a new user within the MySQL shell: CREATE USER 'newuser'@'localhost' IDENTIFIED BY 'password'; Sadly, at this point newuser has no permissions to do anything with the databases.

Therefore, the first thing to do is to provide the user with access to the information they will need. GRANT ALL PRIVILEGES ON * . * TO 'newuser'@'localhost'; The asterisks in this command refer to the database and table (respectively) that they can access—this specific command allows to the user to read, edit, execute and perform all tasks across all the databases and tables. MySQL :: MySQL 5.7 Reference Manual :: 3.3.3 Loading Data into a Table. 3.3.3 Loading Data into a Table After creating your table, you need to populate it. The LOAD DATA and INSERT statements are useful for this. Suppose that your pet records can be described as shown here. (Observe that MySQL expects dates in 'YYYY-MM-DD' format; this may be different from what you are used to.)

Because you are beginning with an empty table, an easy way to populate it is to create a text file containing a row for each of your animals, then load the contents of the file into the table with a single statement. You could create a text file pet.txt containing one record per line, with values separated by tabs, and given in the order in which the columns were listed in the CREATE TABLE statement. Whistler Gwen bird \N 1997-12-09 \N To load the text file pet.txt into the pet table, use this statement: mysql> LOAD DATA LOCAL INFILE '/path/pet.txt' INTO TABLE pet; mysql> LOAD DATA LOCAL INFILE '/path/pet.txt' INTO TABLE pet -> LINES TERMINATED BY '\r\n';

SQL Tutorial - Learn SQL Query Programming Language. SQL (Structured Query Language) is a computer language aimed to store, manipulate, and query data stored in relational databases. The first incarnation of SQL appeared in 1974, when a group in IBM developed the first prototype of a relational database. The first commercial relational database was released by Relational Software (later becoming Oracle). Standards for SQL exist. However, the SQL that can be used on each one of the major RDBMS today is in different flavors. This is due to two reasons: 1) the SQL command standard is fairly complex, and it is not practical to implement the entire standard, and 2) each database vendor needs a way to differentiate its product from others.

In this tutorial, such differences are noted where appropriate. This SQL programming help site lists commonly-used SQL statements, and is divided into the following sections: For each command, the SQL syntax will first be presented and explained, followed by an example. PouchDB, the JavaScript Database that Syncs! TaffyDB - The JavaScript Database.

Louischatriot/nedb. PhpMyAdmin. Aide mémoire SQL. SQLite Home Page. PostgreSQL 9.4.0 - Documentation. MariaDB. The MongoDB 2.6 Manual — MongoDB Manual 2.6.7. Apache CouchDB. The Apache Cassandra Project. NoSQL : arrêtons de dire n’importe quoi. J’ai regardé le mouvement NoSQL évoluer au fil des années.

On y retrouve à peu près tout ce qui fait l’informatique depuis que le monde IT est monde : brillance et troll, hype et génie, utile et gadget, buzz et fact, sam et max, etc. De plus on peut mettre n’importe quoi sous le label NoSQL, et du coup ça a été fait. En fait un fichier est déjà une base de données NoSQL :) Mais rant mise à part, des projets comme redis, riak, elastic search ou mongodb changent vraiment la donne. Malheureusement, tout comme d’autres technos du moment (prog asychrone, tout-http, pre-processeurs, generateurs…), les gens ont tendance à l’utiliser comme la barre de fer, la silver bullet, le passe-partout, le tournevis sonique, bref, le truc à tout faire. L’adage populaire dit “quand on a un bon marteau, tous les problèmes ressemblent à des clous”.

Or, je constate qu’au dessus de ça, les dev appliquent aussi souvent le dicton préféré d’un de mes colocs : “arrête de taper si fort, prend un plus gros marteau”. L’embarras du choix - Comment choisir la bonne plate-forme pour Big Data / Hadoop ? Cette année, le big data est devenu un sujet pertinent dans beaucoup d’entreprises. Bien qu'il n’y ait pas de définition standard du terme “big data”, Hadoop est de facto un standard pour le traitement big data. Presque tous les grands éditeurs de logiciels tels que IBM, Oracle, SAP et même Microsoft utilisent Hadoop. Cependant une fois que vous avez choisi d’utiliser Hadoop, la première question à se poser est de savoir comment débuter et quel produit choisir pour vos traitements big data.

Plusieurs alternatives existent pour installer une version d’Hadoop et réaliser des traitements de ces données. Cet article présente ces différentes alternatives et recommande à quel moment les utiliser. Alternatives de plates-formes Hadoop L’illustration suivante montre différentes alternatives de plates-formes Hadoop. Dans le paragraphe qui suit, nous nous attarderons sur les différentes alternatives en commençant par Apache Hadoop.

Apache Hadoop Problème 1: installation d’un cluster complexe Apache :