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Showing entries 1 to 10 of 70 10 Older Entries

Displaying posts with tag: data (reset)

Importing related MySQL tables into an Excel Data Model using MySQL for Excel
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In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0. 

Importing MySQL data into Excel is a common and important operation in MySQL for Excel. There may be times when you need to analyze the data stored in several MySQL tables or views, (possibly in an ExcelPivotTable which will be the subject of a future blog post), and to do it you need to dump the data into Excel as the first step. Starting with MySQL for Excel 1.3.0 we introduced a feature that allows you to import the data from multiple MySQL tables or views …

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Showing all available MySQL data types when creating a new table with MySQL for Excel
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In this blog post we are going to talk about one of the features included since MySQL for Excel 1.3.0, a new advanced option was added to the Export Data dialog to show all available MySQL data types on its Data Type combo-box to override its default behavior that shows only the most commonly used data types.

Remember you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer Zone.

Optimistic updates for Edit Data operations in MySQL for Excel
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In this blog post regarding MySQL for Excel features included since version 1.2.0, we are going to talk about a new option that is used along with Edit MySQLData operations; very useful when editing data in a multi-user environment. If you are not familiar with editing MySQL data it is very advisable that you visit our thorough blog post about that topic: How To - Guide to editing MySQL data within Excel.

Remember you can install the latest GA or maintenance version using …

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How to structure and design a relational database to support you data storage needs?
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Well, every now and then, when we began to start a new project or app, which has some data storage requirement, we have a deep intriguing thought as to how best represent the data structure so as to support a variety of needs including but not limited to (ACID rules):

1. Normalization
2. Reliability
3. Consistency
4. And many others

Below, I provide a set of steps which you can follow to arrive at a data model that correctly suites your requirements.

Steps:

1. Identify the project or app requirements / …










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How To - Guide to exporting data from Excel to a new MySQL table
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There may be times when you need to create a new table in MySQL and feed it with data from another database, the Internet or from combined data sources. MS Excel is commonly used as the bridge between those data sources and a target MySQL database because of the simplicity it offers to organize the information to then just dump it into a new MySQL table. Although the last bit sounds trivial, it may actually be a cumbersome step, creating ODBC connections within Excel through Microsoft Query may not help since these are normally created to extract data from MySQL into Excel, not the …

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Anonymizing Data During Replication
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If you happen to work with personal data, chances are you are subject to SOX (Sarbanes-Oxley) whether you like it or not.

One of the worst aspects of this is that if you want to be able to analyse your data and you replicate out to another host, you have to find a way of anonymizing the information. There are of course lots of ways of doing this, but if you are replicating the data, why not anonymize it during the replication?

Of the many cool features in Tungsten Replicator, one of my favorites is filtering. This allows you to process the stream of changes that are coming from the data extracted from the master and perform operations on …

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SQL to Hadoop and back again, Part 2: Leveraging HBase and Hive
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The second article in a series covering Big Data and SQL interaction is available now:

“Big data” is a term that has been used regularly now for almost a decade, and it — along with technologies like NoSQL — are seen as the replacements for the long-successful RDBMS solutions that use SQL. Today, DB2®, Oracle, Microsoft® SQL Server MySQL, and PostgreSQL dominate the SQL space and still make up a considerable proportion of the overall market. Here in Part 2, we will concentrate on how to use HBase and Hive for exchanging data with your SQL data stores. From the outside, the two systems seem to be largely similar, …

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What’s the data on the 3Ci Data Team?
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3Ci processes over a billion transactions a month. More than 100 million unique U.S. consumers have engaged with a business through our platform. All that activity creates massive amounts of data. The Data Team at 3Ci is responsible for keeping our offerings running at optimal performance and for making sense of our data. They manage MySQL [...]

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Announcing the MySQL Applier for Apache Hadoop
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Enabling Real-Time MySQL to HDFS Integration

Batch processing delivered by Map/Reduce remains central to Apache Hadoop, but as the pressure to gain competitive advantage from “speed of thought” analytics grows, so Hadoop itself is undergoing significant evolution. The development of technologies allowing real time queries, such as Apache Drill, Cloudera Impala and the Stinger Initiative are emerging, supported by new …

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Data Organization in InnoDB
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Introduction

This article will explain how the data is organized in InnoDB storage engine. First we will look at the various files that are created by InnoDB, then we look at the logical data organization like tablespaces, pages, segments and extents. We will explore each of them in some detail and discuss about their relationship with each other. At the end of this article, the reader will have a high level view of the data layout within the InnoDB storage engine.

The Files

MySQL will store all data within the data directory. The data directory can be specified using the command line option –data-dir or in the configuration …

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Showing entries 1 to 10 of 70 10 Older Entries

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