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I want to write few process intensive back-end scripts for a web application using Perl and MySQL.
I will be frequently using embedded SQL in my scripts. Can anyone suggest a structured way to do that. I feel it will take lot of time to create generic classes for tables, if I have to use tables as classes and create functions like Add, Update or find to run Insert, update or select statements. Also such code itself will be quite vast than my actual business code. On the other side I do not want to use unstructured queries spread allover the code.
Are there any inbuilt class libraries to take care of my needs.
Any suggestions are greatly appreciated.
DBIx::Class is the best in class for an object-relational mapper in Perl. It will take care of all the SQL to add, update, delete and search and will do it efficiently. You tell it the tables, columns, keys and relationships. DBIx::Class::Schema::Loader can even do that part for you.
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I have a program with a priority queue (PQ) so huge that it does not fit to the memory. It was decided to move some data to MySQL database (DB) in following way: the new elements are put into DB instead of PQ, and when the PQ is emptied, it is updated by the entries in the DB. But this way appeared to spoil the priority ordering. Is there any solution which does not corrupt the priority ordering and combines PQ with DB?
For some reason I cannot get rid of PQ and use only DB.
Your question is rather vague on the functionality, but I think the idea is wrong.
Someone seems to have the idea of using the database as secondary storage for an in-memory application. That doesn't really make much sense. Normally, you would use a simple file for this. Although you can use a database for managing secondary/tertiary storage, a database does many other things, so it is like using a smart phone only as a clock.
If you are going to use a database, then store the entire structure in the database and develop an API for it that meets your needs.
If you want help with how to structure the data, then write another question and include:
sample data
how the priority queue will be used
any ideas you have on the data structure
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Hi I am pretty new to NodeJS. I have worked with the MongoDB using the mongoose module. Now I am using MySQL for my current project and am trying to figure out the best options for ORM using MySQL. I have come across BookShelf.JS (with Knex.JS) node-orm2 and Squel.js
Has anyone used any of these or something else for a NodeJS MySQL/PostgreSQL/SQLite3 ?
Personally, I love Bookshelf. This question might be a little too subjective for SO, but I'll try to give a decent answer:
Knex is a joy. It's a straightforward interface, reminiscent of Laravel's query builder.
Bookshelf is a joy. It's a straightforward interface, reminiscent of Laravel's Eloquent ORM.
For most (not-too-big-and-probably-not-Node-appropriate) projects, Bookshelf/Knex will be all you need. They're easy to get running, and the codebases aren't too big if you decide that you need to work something out for yourself that isn't in the documentation.
Source: personal experience with a couple of the options. I've always found my way back to Bookshelf, though.
Take a look at Sequelize, I use it and recommend. It supports all databases you described.
Squel.js isn't a ORM framework, and it's very useful for complex queries, I use it with SequelizeJS.
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I'm using mysql for my database needs and the total size is ~1.5 TB.
I'm looking for a Business intelligence tool which gives me an interface to fetch reports in any desired format to help decision making. The user shall be able to sum, sort, count, sum in various ways.
I don't know what shall I do about it.
In the past few days, I've read dozen of articles and watched many videos about Bigdata, hadoop, BIRT, Solr, Cassandra, mongodb, noSql and just everything that popped in search suggestions for my queries on BI but can't decide what's the right tool for me.
Is there a tool available to help me with my Data reporting and visualizing needs?
Did you read about Tableau (http://www.tableausoftware.com/)? Its a very nice data visualization tool (though not free but worth it) and can connect to various data sources (mysql, hive etc). Also it provides options to do all such operations you mentioned. It will be worth to evaluate it once.
It provides a 15 day free version. You can try out and see if it fits your needs.
Try Google Big Query, it should solve your issue
https://cloud.google.com/bigquery/
For syntax, please refer
https://cloud.google.com/bigquery/query-reference
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I am writing a database application in C linux. Currently I work on mysql but later we might migrate to postgres. Therefore my boss has asked my to prepare the application to be able to use either of the databases(mysql or postgres).
Is there a free api which I can use for this purpose? Or any suggestion on how best I can do this?
The official answer to that is ODBC.
If you don't like that (and let's face it, no one really does), Qt has a database access module, QtSql. Obviously, this will require you to make heavy use of Qt in your application.
If you can find drivers for your platform, ODBC was supposedly meant to provide exactly this: a platform-independent way to talk to databases.
(I say supposedly because in my experience, ODBC is such a mess that hooking up to an ODBC driver once turned out to be more difficult than just writing the code three times for three different databases.)
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What is the best FREE solution to implement one ETL project in MySql?
I need to extract for analisys big amount of data, and put the results in other tables.
Regards,
Pedro
Pentaho Kettle (PDI) is open source and it has a community version here, which works quite good.
Talend also does an excellent job for ETL and ELT. You can take a look at this page on my website: http://www.hiregion.com/2010/01/data-loading-through-talend-etl-studio.html and related articles. I have also loaded hundreds of thousands of rows to millions through MySQL bulk loading (LOAD DATA INFILE syntax - dev.mysql.com/doc/refman/5.1/en/load-data.html ) and then doing some transformations in MySQL. You can do most of transformations before the load (ETL) or after load (ELT) or use hybrid technique.