Image
EAN-13	0024543011415
UPC-A	024543011415
Product Name	Python
Category	Electronics / Photography: A/V Media: Movie / TV
Short Description	DVD
Amazon.com	Buy on Amazon ~ B000053VC7
SKU	02454301141U
Price New	29.99 US Dollars    (curriencies)
Price Used	1.99 US Dollars    (curriencies)
Rating	R - Restricted
IMDb
Run Time	99 minutes
Aspect Ratio	1.85:1
Cast	Casper Van Dien, Dana Barron, Frayne Rosanoff, Robert Englund, William Zabka
Run Time	99 minutes
Width	5.5 inches    (convert)
Height	0.5 inches    (convert)
Length	9 inches    (convert)
Weight	25 hundredths pounds    (convert)
Binding	Dvd
Format	Anamorphic, Closed-captioned, Color, Dolby, NTSC
Run Time	99 minutes
Long Description	Scientist Dr. Anton Rudolph (Englund) has engineered the perfect killing machine - the world's first massive, genetically enhanced python. Mistakenly unleashed in a small American town, this unstoppable creature with a voracious appetite is raging out of control. As the massive python gobbles up the locals one by one, it's up to Special Agent Parker (Van Dien) to conquer nature's ulitmate terror. If you enjoyed movies like Lake Placid and Anaconda, you'll eat up PYTHON.
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Created	07-01-2006
Modified	04-28-2020 4:40:31pm
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SHA256	a2d382e12ac2079412057c9037d46e86f35f659e42d76981585636197e9dc0dc
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Article of interest

Here we will demonstrate the most basic example of importing the CSV data files that we produce on this site into your MySQL database.

For information about various databases you can use and how to import CSV files into them, please view the overview article "Importing CSV data into your database".

For this example, we are going to import the product data CSV file out of the sample_ean_data.zip but this same process will work on the full data download file. We will also be executing the commands in the MySQL Workbench but you can also use the command line tool with the same commands if you like.

First, start by creating a blank table. Use the table layout described in the read_me file for the most up-to-date table layout. It is suggested that you not use any indexing at this point. You can add indexes later. It is most likely that you will have your own tables where you want to store your data so importing the CSV files can be done into temporary tables and then later copied over to your tables. Leaving off the indexes and constraints on these import tables reduces the risk of import errors. Here is an example:

create table ean_product
(
    EAN13             varchar(13),
    UPCA              varchar(12),
    UPCE              varchar(8),
    SKU               varchar(200),
    PriceNew          numeric(15,2),
    PriceUsed         numeric(15,2),
    PriceDate         date,
    company           varchar(13),
    product           varchar(100),
    description       varchar(100),
    category          int,
    url               varchar(500),
    created           datetime,
    modified          datetime
);


Next we perform the import using the LOAD DATA INFILE command. The path to the file depends on where you saved the data and which operating system you are on. For Windows users you might find your file on the C: drive and Linux users may find your date in your home (~) folder. This example shows a Linux import. Only the path would be different between the operating systems.

LOAD DATA LOCAL
    INFILE '~/sample_ean_data/sample_ean_product.csv' 
    INTO TABLE ean_product
    FIELDS TERMINATED BY ',' ENCLOSED BY '"' ESCAPED BY '\\'
    LINES TERMINATED BY '\r\n'
    IGNORE 1 LINES;


Finally, lets look at the data that we just imported.

SELECT * FROM EAN_PRODUCT;


You may have seen some warnings after the import command. If you are concerned about these warnings, examine the data. It could be that some data has grown beyond the size specified in the read_me file. If you are worried, make the fields larger and try the process again after deleting all of the data out of the table.