Image
EAN-130888574106638   EAN-13 barcode 0888574106638
UPC-A888574106638   UPC-A barcode 888574106638
Product NameAngel Face
CategoryElectronics / Photography: A/V Media: Movie
Amazon.comA Buy on Amazon ~ B00Q7LT9NA
ModelB00Q7LT9NA
Price New12.82 US Dollars    (curriencies)
Price Used12.92 US Dollars    (curriencies)
Run Time91 minutes
CastJean Simmons, Mona Freeman, Robert Mitchum
Run Time91 minutes
Width5.5 inches    (convert)
Height0.5 inches    (convert)
Length7.5 inches    (convert)
Weight22 hundredths pounds    (convert)
BindingDvd
FormatNTSC
Published12/23/2014
Run Time91 minutes
FeaturesFactory sealed DVD
Long DescriptionOtto Preminger, who showed how to mix a beautiful woman with murder in the landmark Laura, directs this tale of a passion gone haywire. Frank's a regular guy with a steady girl and a dream of owning his own garage when he crosses paths with Diane. She wants him. Or does she want a fall guy to blame when Diane's stepmother plunges off a high cliff and leaves her fortune to Diane? Alibis, betrayals, courtroom thrills and the fire of a woman too dangerous to trust and too alluring to resist make Angel Face a film-noir classic.

When sold by Amazon.com, this product will be manufactured on demand using DVD-R recordable media. Amazon.com's standard return policy will apply.

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Created04-14-2018 2:32:49am
Modified04-14-2019 1:59:32pm
MD58b27ae414d93113c1d5130ddb6d2a55d
SHA2568ecaf4f8ad1d73d71a8db32ad70a793fcfca7d2dfdfc73fcbc07cfbb084ee75b
Search Googleby EAN or by Title
Query Time0.0122988

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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