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EAN-130012236130437   EAN-13 barcode 0012236130437
UPC-A012236130437   UPC-A barcode 012236130437
Product NameRed Heat
LanguageEnglish
CategoryElectronics / Photography: A/V Media: Movie / TV
Short DescriptionDvd
Amazon.comA Buy on Amazon ~ B0002J58HO
Model2209621
Price New5.50 US Dollars    (curriencies)
Price Used1.41 US Dollars    (curriencies)
RatingR - Restricted
IMDbIMDb Link
TrailerWatch The Trailer
Run Time104 minutes
Aspect Ratio1.85:1
CastArnold Schwarzenegger, Jim Belushi, Peter Boyle, Ed O'Ross
DirectorWalter Hill
GenreACTION,COMEDY,CRIME
Width5.5 inches    (convert)
Height0.5 inches    (convert)
Length7.75 inches    (convert)
Weight4.8 ounces    (convert)
BindingDvd
Release Year1988
FormatMultiple Formats, Anamorphic, Closed-captioned, Color, Dolby, NTSC, Special Edition, Subtitled, Widescreen
Published09/01/2004
Run Time104 minutes
FeaturesFactory sealed DVD
Long DescriptionArnold Schwarzenegger plays a Russian policeman sent after a Georgian drug dealer who has escaped to the United States and is awaiting extradition in Chicago. Jim Belushi plays his temporary partner on the Chicago police. When the drug dealer escapes, the two police must overcome their differences in order to recapture him.
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Created08-16-2006
Modified05-17-2019 10:07:31am
MD50006f2f7cf08a45d4d987e14273b30a7
SHA2569f620a019622c47caf3931731968fb38b8a634f48e1db4b667008dc4a4b2ccf9
Search Googleby EAN or by Title
Query Time0.0284932

An article of interest

Making use of the tools we offer

Importing our data into your MySQL database

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.