Image
EAN-130826663187335   EAN-13 barcode 0826663187335
UPC-A826663187335   UPC-A barcode 826663187335
Product NameOf Unknown Origin
CategoryElectronics / Photography: A/V Media: Movie / TV
Amazon.comA Buy on Amazon ~ B079NBPNWS
Price New21.63 US Dollars    (curriencies)
RatingR - Restricted
IMDbIMDb Link
Run Time88 minutes
Aspect Ratio1.85:1
CastPeter Weller, Jennifer Dale, Lawrence Dane, Kenneth Welsh
DirectorGeorge P. Cosmatos
GenreHORROR
Run Time89 minutes
Width7.5 inches    (convert)
Height5.4 inches    (convert)
Length0.7 inches    (convert)
Weight25 hundredths pounds    (convert)
BindingBlu-ray
Release Year1983
FormatNTSC, Widescreen
Run Time89 minutes
Long DescriptionBart Hughes has a pretty good life, a beautiful wife, a young son, a good job with promotion prospects, and a renovated brownstone in New York. When wife and kid leave for a vacation, Bart stays behind to work on a project that will earn him that promotion, unaware that a certain inhabitant of his basement has other plans for his time. Bart goes a bit bonkers trying to kill this rat, destroying most of his house in the process. Certain allegorical elements tie the household conflict to the "rat race" in his office, but the main event is certainly the night-and-day contest of wills between man and rodent.
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Created04-14-2018 1:37:37am
Modified05-22-2019 12:51:29pm
MD5d3763257bd1acd8947959385714d6046
SHA256fcd7bfddbad68b5618bd3f8aa5168e94c1e722cb80e5b73b372d334add664f58
Search Googleby EAN or by Title
Query Time0.0262251

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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