EAN-130828970124997   EAN-13 barcode 0828970124997
UPC-A828970124997   UPC-A barcode 828970124997
Product NameNamastey London DVD
CategoryElectronics / Photography: A/V Media: Movie / TV
Amazon.comA Buy on Amazon ~ B000R939DY
Long DescriptionThe Indian population and community is present all thorough the world. And a substantial part of this resides in Britain; some of them who have been there ever since the times of the British Raj in India. However, the elder generations have not forgotten their identities and the place they believe that their roots are instilled inn. But much to their dismay, that is not the case with the younger Generation that has been born there and has been influenced by the surrounding that they have grown up inn. Our Story revolves around one such girl who has been born and brought up in the heart of London Jasmine alias Jazz cause that's the name that she goes by and prefers being called; has already been through hoardes of eligible suitors that have approached her through the recommendation of her father; and made sure that she has gotten rid of them in one way or another. The primary reason being that Jazz is not interested in being tied down by a typical Indian male but would rather be with a white man who she feels would be more in tune with her way of thinking and lifestyle. That's why she has uncanny closeness for her boss namely Charlie brown, who has been through three divorce settlements already and is now looking for the fourth Mrs. Brown. Charlie brown too reciprocates the some feelings towards jazz. ~ ~ Released Year : 2007 ~ Running Time : approx 132 mins. ~ Color B/W : Color ~ Language : Hindi ~ SubTitles : English Subtitles
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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 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.

    INFILE '~/sample_ean_data/sample_ean_product.csv' 
    INTO TABLE ean_product

Finally, lets look at the data that we just imported.


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.