Image
EAN-13	0888574722630
UPC-A	888574722630
Product Name	Dracula A.D. 1972
Category	Electronics / Photography: A/V Media: Movie / TV
Amazon.com	Buy on Amazon ~ B07HGKPFHS
Price New	21.99 US Dollars    (curriencies)
Rating	PG - Parental Guidance Suggested
IMDb
Run Time	96 minutes
Cast	Christopher Lee, Peter Cushing, Stephanie Beacham, Christopher Neame
Director	Alan Gibson
Genre	HORROR
Run Time	96 minutes
Width	5.5 inches    (convert)
Height	0.5 inches    (convert)
Length	7.5 inches    (convert)
Weight	37 hundredths pounds    (convert)
Binding	Blu-ray
Release Year	1972
Format	Blu-ray
Run Time	96 minutes
Long Description	In London 1872 - the final battle between Lawrence van Helsing and Count Dracula on top of a coach results in Dracula dying from a stake made from the remains of a wooden wheel. Lawrence dies from his wounds and, as he is buried, a servant of Dracula buries the remains of the stake by the grave and keeps a bottle of Dracula's ashes and the ring. One hundred years later, the colourful 1972, Johnny, the great-grandson of the servant joins up with a "group" containing Jessica, the grand-daughter of the present vampire hunter, Abraham van Helsing and with their unknowing help resurrect Dracula in the 20th Century who is determined to destroy the house of Van Helsing, but who can believe that The king of the Vampires really exists and is alive - in 20th Century London?
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Created	09-27-2018 12:01:54am
Modified	06-02-2019 5:21:30pm
MD5	affa327d5a0e6ffee0a7bb7f8bbf0bba
SHA256	2d988f64b64d0066b3dce22d6c2c742a4ee127c46fd7c4aab7c5353bec917f46
Search Google	by EAN or by Title
Query Time	0.0195751

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.