Image
EAN-130826663164794   EAN-13 barcode 0826663164794
UPC-A826663164794   UPC-A barcode 826663164794
Product NameMidnight Run
CategoryElectronics / Photography: A/V Media: Movie
Amazon.comA Buy on Amazon ~ B0185X2BJ6
Model35497335
Price New21.97 US Dollars    (curriencies)
Price Used21.96 US Dollars    (curriencies)
RatingR - Restricted
IMDbIMDb Link
Run Time126 minutes
CastRobert De Niro, Charles Grodin, Yaphet Kotto, John Ashton
DirectorMartin Brest
GenreACTION,COMEDY,CRIME
Run Time127 minutes
Width5.25 inches    (convert)
Height0.3 inches    (convert)
Length6.5 inches    (convert)
Weight15 hundredths pounds    (convert)
BindingBlu-ray
Release Year1988
FormatCollector's Edition, NTSC, Widescreen
Run Time127 minutes
Long DescriptionBounty hunter Jack Walsh (Robert De Niro) is sent to find and return bail jumper and former Mafia accountant, Jonathan "The Duke" Mardukas (Charles Grodin). The FBI has had no success in locating The Duke, so when Jack finds him in next to no time, they are a little embarrassed. In order to collect his $100,000 fee, Jack must take The Duke from New York to Los Angeles. However, the Mafia and the FBI have other ideas, as does Marvin Dorfler (John Ashton), a rival bounty hunter. On their long cross-country trip to LA, the two get to know each other and they build up a strange friendship.
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Created04-22-2018 4:31:52am
Modified05-29-2019 10:37:37am
MD516fd49107d0c9b8a08c96d94b7390425
SHA2563346156b3ebdd8934822b7b02e63f24ccbce8ff3abdb144adca54a3000055592
Search Googleby EAN or by Title
Query Time0.0227339

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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