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EAN-139780747810438   EAN-13 barcode 9780747810438
Product NamePottery of the Southwest: Ancient Art and Modern Traditions (Shire Library USA)
LanguageEnglish
CategoryBook / Magazine / Publication
Short DescriptionHeight:8.27 inches / Length:5.87 inches / Weight:0.5 pounds / Width:0.31 inches
Amazon.comA Buy on Amazon ~ 0747810435
SKUY9780747810438
Price New6.41 US Dollars    (curriencies)
Price Used3.22 US Dollars    (curriencies)
Width0.19 inches    (convert)
Height8.23 inches    (convert)
Length5.89 inches    (convert)
Weight8 ounces    (convert)
AuthorCarol Hayes, Allan Hayes
Page Count64
BindingPaperback
Published02/21/2012
Long DescriptionFor almost two thousand years, the pottery made by the Indians of America's Southwest has remained a vital art. Today, more than twenty Pueblos and tribes make pottery within the tradition, each with a distinctive style. Many of those local styles have persisted for hundreds of years. In prehistory, beautiful pieces had high trade value, and the finest contemporary pieces command prices appropriate to fine art of any type. Potters like Nampeyo, Maria Martinez and Juan Quezada achieved worldwide fame. Yet despite its history and the skill of its artists, Southwestern Indian pottery remains surprisingly easy to collect. This book introduces the art from its beginnings to the present and displays examples that describe how America's first important art form grew into one of the world's most accessible treasures.
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Created11-22-2012 2:06:03am
Modified10-07-2017 7:49:54am
MD552494dd025e6b5a68d7a7bfc8dd524d2
SHA256ca58ef4efb779092ec902da032bc0ad8934553d3a04aae2b1802ee2c142dc4b9
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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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