| Image |  |
| EAN-13 | 0043396421622  |
| UPC-A | 043396421622  |
| Product Name | Devil in a Blue Dress / Glory / Philadelphia / Taking of Pelham 1 2 3 |
| Language | English |
| Category | Electronics / Photography: A/V Media: Movie / TV |
| Amazon.com |  Buy on Amazon ~ B00DDT0J92 |
| Price New | 5.00 US Dollars (curriencies) |
| Price Used | 4.65 US Dollars (curriencies) |
| Width | 5.25 inches (convert) |
| Height | 0.5 inches (convert) |
| Length | 7.5 inches (convert) |
| Weight | 3.2 ounces (convert) |
| Binding | Dvd |
| Long Description | Devil in a Blue Dress - Denzel Washington stars as an L.A. private eye, 'Easy' Rawlins, who is caught between the power elite and a beautiful dame's shocking secret. Glory - Matthew Broderick and Denzel Washington star in this inspiring story of the first black regiment to fight for the North in the Civil War. Philadelphia - Emotional powerhouses Tom Hanks and Denzel Washington star as competing lawyers who sue a prestigious law firm for AIDS discrimination. Taking of Pelham 1,2,3 - Starring Denzel Washington and John Travolta, this film is about a New York City subway dispatcher whose ordinary day is thrown into chaos by an audacious crime: the hijacking of a subway train. |
| Similar Items | 0883929135950: Malcolm X 0883904123880: Denzel Washington Triple Feature: For Queen and Country / The Mighty Quinn / Out of Time 0024543987710: Man on Fire / Out of Time / Unstoppable / The Seige Quad Feature 0024543423614: Man on Fire / Out of Time 0024543410683: Rising Sun / Sugar Hill 0024543139683: Man On Fire Qv (Ws) (Frn) |
| Created | 01-09-2015 7:52:04pm |
| Modified | 01-03-2020 10:24:04pm |
| MD5 | e9e6cfe7189940d0197b7b72cef37afb |
| SHA256 | 3644549e3bfad7e7b0067cdbb52edb4d58831a9e6fd9dd9449f64d840b327003 |
| Search Google | by EAN or by Title |
| Query Time | 0.1065111 |
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.