Image
EAN-13	9780743400008
Product Name	Murder On The Yellow Brick Road (Toby Peters Mysteries)
Language	English
Category	Book / Magazine / Publication
Amazon.com	Buy on Amazon ~ 0743400003
SKU	MON0001910528
Price New	23.95 US Dollars    (curriencies)
Price Used	3.00 US Dollars    (curriencies)
Width	0.53 inches    (convert)
Height	8.16 inches    (convert)
Length	5.42 inches    (convert)
Weight	6.08 ounces    (convert)
Author	Stuart M. Kaminsky
Page Count	192
Binding	Paperback
Published	05/01/2000
Features	Used Book in Good Condition
Long Description	The year is 1940 and Los Angeles-based private eye Toby Peters has been asked to track down a murderer stalking the back lots of one of Hollywood's most powerful movie companies. This is the first paperback publication of a noir classic which has been out of print for over 12 years.
Similar Items	9780446400619: Bullet for a Star (Toby Peters Mysteries) 9780892964116: Poor Butterfly 9780786710232: To Catch A Spy: A Toby Peters Mystery 9780445409095: The Man Who Shot Lewis Vance: A Toby Peters Mystery 9780446404402: Think Fast, Mr. Peters (A Toby Peters Mystery) 9780446401913: He Done Her Wrong (A Toby Peters Mystery) 9780783891019: You Bet Your Life 9780312396176: The Howard Hughes Affair 9780445409064: You Bet Your Life 9781453236802: Bullet for a Star (The Toby Peters Mysteries) View 11 more similar items
Created	11-20-2012 5:19:30am
Modified	09-02-2017 3:29:43pm
MD5	9864e9b0ae78abdfe6f7a04c66f99706
SHA256	f588790580c86471a90e7ddf42307f76ddfb9db0ec5b67da7b105553490e9391
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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 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.