Image
EAN-130000000634816   EAN-13 barcode 0000000634816
UPC-A000000634816   UPC-A barcode 000000634816
Product NameManchester City Fc Personalized Mug - Soccer Gifts
CategoryCleaning Supplies / Equipment
Short Description8.11oz (230g)
Amazon.comA Buy on Amazon ~ B0055N5R1Y
Price New14.99 US Dollars    (curriencies)
Weight4.96 ounces    (convert)
BindingKitchen
Features
  • Your Name and Number on the Man City Shirt in the Etihad Dressing Room - Brilliant Gift!!
  • Email your Surname and Number when purchasing
  • Max 12 Characters (including spaces) any number from 1 to 99
  • Mug Height 9cm Dia 8cm - Dishwasher Safe
  • Great Unique Soccer Gift
Long DescriptionPersonalised Manchester City FC Mug Your Name and Shirt No In The City Dressing Room Appear alongside Man City Superstars. We merge your Surname and chosen number onto the centre shirt in the Official Manchester City dressing room. Displayed on a quality, durable mug, this superb full-colour design is guaranteed to make you the envy of the office. NOTE! WHEN YOU HAVE MADE YOUR PURCHASE DONT FORGET TO EMAIL THE SURNAME AND YOUR SHIRT NUMBER YOU WOULD LIKE ON THE MUG 12 Characters maximum (including spaces) Players' names will be modified on this product to reflect any changes. Please note that we cannot accept returns on this item as it will have been personalised with your details. We can't sell it again you see. Refunds only for non-delivery after 10 working days from shipment Officially Licensed Products
Created05-22-2010
Modified02-17-2017 2:12:04am
MD577500efd3cfbcfc50e01d398e28dc91a
SHA256fda6db61c684568222244c11ba3689ef11ab1dec88554851922a4654edde0ed9
Search Googleby EAN or by Title
Query Time0.0057070

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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