Image
EAN-139780756929756   EAN-13 barcode 9780756929756
Product NameHannah, Divided
CategoryBook / Magazine / Publication
Short DescriptionPrebound
Amazon.comA Buy on Amazon ~ 075692975X
SKU947730
AuthorAdele Griffin
BindingHardcover
Published07/01/2004
Long DescriptionThirteen-year-old Hannah Bennett loves her life in Chadds Ford. She goes to school, helps out with her family's dairy farm, jumps rope, and listens to favorite radio programs with her friends. Although she has difficulty reading, she does have one area of special talent: numbers. Her gift for math means that she does all of the invoicing for the farm, and helps out the younger students in their one-room schoolhouse. Best of all, Hannah enjoys a special relationship with Granddad McNaughton, who shares her passion for counting and calculating. He thinks of her gift as the key to a greater future elsewhere. 'You'll rust here,' he predicts. But Hannah can't imagine life anywhere else. Then Hannah is offered a rare opportunity for a country girl in 1934: to test for a scholarship to attend a private school in Philadelphia. Over her parents' objections, Hannah goes. But life in a big city is harder and lonelier than she'd ever imagined. Just when things seem at their worst, Hannah must somehow find the courage to decide what she values most. Acclaimed author Adele Griffin's first historical novel is a funny and poignant story of one girl's journey to her bravest self.
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Modified09-14-2017 7:02:31am
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SHA25602e623222ab602eb6b135eac55aa739499ecd87762ef6e0a285ba5f2bc0f875c
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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.

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