Image
EAN-130012569731028   EAN-13 barcode 0012569731028
UPC-A012569731028   UPC-A barcode 012569731028
Product NameNeverending Story/Neverending Story 2
LanguageEnglish
CategoryElectronics / Photography: A/V Media: Movie
Short Description1 Double Sided Disc
Amazon.comA Buy on Amazon ~ B00G4DQ36C
Price New9.97 US Dollars    (curriencies)
Price Used5.70 US Dollars    (curriencies)
Run Time181 unknown-units
GenreCHILDREN/FAMILY
Run Time181 unknown-units
Width0.4 inches    (convert)
Height5.25 inches    (convert)
Length7.25 inches    (convert)
Weight18 hundredths pounds    (convert)
BindingDvd
Run Time181 unknown-units
Long DescriptionWhen a 10 year old Bastian open the mysterious, ornately bound book entitled The Neverending Story, he never imagined he will be transported into its amazing world on Fantasia and become the hero of its even more amazing tale. Now you can go there too in this magical film full of astonishing creatures and directed by Wolfgang Petersen. Bastian, the Luckdragon and the genial Rock Biter return for more adventure in the spellbinding The Neverending Story II: The Next Chapter from director George Miller. This time, new forces threaten the world of imagination. But they aren't the only foes Bastian faces. He must also overcome problems at home!
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Created06-09-2007
Modified02-13-2019 3:20:44am
MD57951ee14e7b8fe65d11412696e8f7bfd
SHA2563d78b726a9f7590abd38b519ceef1fd4e11f9ed5f2ea23a124b2613a143ad446
Search Googleby EAN or by Title
Query Time0.0342290

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.

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