Image
EAN-139780790799803   EAN-13 barcode 9780790799803
Product NameNBA Ultimate Jordan
CategoryElectronics / Photography: A/V Media: Movie
Amazon.comA Buy on Amazon ~ B0002IKSFC
Price New55.25 US Dollars    (curriencies)
Price Used11.98 US Dollars    (curriencies)
IMDbIMDb Link
Run Time330 minutes
CastCharles Barkley, Jack Haley, Magic Johnson, Michael Jordan, Phil Jackson
Run Time330 minutes
Width5.5 inches    (convert)
Height1 inches    (convert)
Length7.5 inches    (convert)
Weight50 hundredths pounds    (convert)
BindingDVD
FormatBox set, Closed-captioned, Collector's Edition, Color, NTSC
Published09/05/2018
Run Time330 minutes
Featuresinteractive DVD-Rom features
Long DescriptionMarking 20 years since Michael Jordan's celebrated arrival in the NBA, this truly historic 3-disc Collector's Edition chronicles the amazing career of this great American icon. For the first time ever, exclusive to this set, are Jordan's five all-time, greatest games in their entirety. Add to this, five #1 best-selling Michael Jordan programs, over an hour of bonus footage including MJ's greatest moves, dunks and shots, plus DVD-ROM features and you have the ultimate tribute to the ultimate sports legend.
Similar Items0012569702813: Charles Barkley - Sir Charles (NBA Hardwood Classics)
0012569598775: Nba Hardwood Heroes
Created08-10-2018 5:42:55am
Modified06-05-2019 4:41:10pm
MD588bc50b6707981a71d5bd544c61df82e
SHA2566c36219c7335624d517f7ae961d349984a3dd5a0ef2bc6d6ede86f984ea79361
Search Googleby EAN or by Title
Query Time0.0085149

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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