Image
EAN-13	0191329041178
UPC-A	191329041178
Product Name	Mamma Mia! Here We Go Again
Category	Electronics / Photography: A/V Media: Movie / TV
Amazon.com	Buy on Amazon ~ B07F9Q4C4X
Price New	22.99 US Dollars    (curriencies)
Cast	Amanda Seyfried, Christine Baranski, Colin Firth, Lily James, Meryl Streep
Width	7.5 inches    (convert)
Height	5.4 inches    (convert)
Length	0.7 inches    (convert)
Weight	52 hundredths pounds    (convert)
Binding	Blu-ray
Long Description	Taking place ten years after the original film, Sophie (Amanda Seyfried) is pregnant while running her mother Donna’s (Meryl Streep) villa. Mamma Mia! Here We Go Again, tells the story of how a young Donna (Lily James) came to start up her villa, met each one of Sophie’s dads, and raised Sophie on her own. Sophie is also faced with an unexpected visit from someone she had not invited or expected to see: her grandmother, Ruby Sheridan (Cher).
Similar Items	0876964016315: Rbg 0841887036795: Masterpiece Poldark, Season 4 Blu-ray 0841887023443: Earth a New Wild 0191329053645: Mamma Mia! The Movie 0191329053638: Mamma Mia! 0031398291763: Hot Summer Nights 0024543610861: I Love You, Beth Cooper
Created	07-28-2018 1:44:12am
Modified	04-10-2020 4:16:27pm
MD5	3115da76803af08d7b7c7163e597138f
SHA256	b335b545df6761f829e0db339ff47d5b80f426443a34c317be0c606e1c989a1d
Search Google	by EAN or by Title
Query Time	0.0142269

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.