Image
EAN-130883929520572   EAN-13 barcode 0883929520572
UPC-A883929520572   UPC-A barcode 883929520572
Product NameLEGO DC Comics Super Heroes Justice League Gotham City Breakout
CategoryElectronics / Photography: A/V Media: Movie / TV
Amazon.comA Buy on Amazon ~ B01E9PF81M
Model35426211
Price New6.42 US Dollars    (curriencies)
Price Used3.82 US Dollars    (curriencies)
Run Time72 minutes
CastEric Bauza, Greg Cipes, Khary Payton, Nolan North, Troy Baker
Run Time72 minutes
Width5.6 inches    (convert)
Height6.8 inches    (convert)
Length1.3 inches    (convert)
Weight25 hundredths pounds    (convert)
BindingBlu-ray
FormatAC-3, Animated, Dolby, NTSC, Widescreen, Multiple Formats
Run Time72 minutes
Long DescriptionLEGO DC Comics Super Heroes: Justice League: Gotham City Breakout w/Figurine (Blu-ray) Batman faces his greatest challenge yet: VACATION! The caped crusader reluctantly agrees to let Batgirl and Nightwing take him on a long overdue vacation from crimefighting, while Superman and the Justice League watch over Gotham City. Neither operation goes as planned when Batman's vacation is cut short by dangers from his past and invaders from the center of the earth, and Superman and the other Leaguers quickly realize just how much Batman usually has his hands full with the villains of Gotham.
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Created04-14-2018 2:10:41am
Modified04-30-2020 8:41:55am
MD5ba5d3c0d5a198d37429c6c5d65eb031f
SHA2565a568cab80063387cc82472cf8347399b77f25ae462ba7820180662223a87b23
Search Googleby EAN or by Title
Query Time0.0149810

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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