EAN-139780713612851   EAN-13 barcode 9780713612851
Product NameEpistles Of Peter And Jude (Black's New Testament Commentaries)
CategoryBook / Magazine / Publication
Short DescriptionHeight:8.66 inches / Length:5.51 inches / Weight:1.17 pounds / Width:0.83 inches
Amazon.comA Buy on Amazon ~ 0713612851
Price New67.51 US Dollars    (curriencies)
Price Used12.49 US Dollars    (curriencies)
Width0.82 inches    (convert)
Height8.5 inches    (convert)
Length5.5 inches    (convert)
Weight16.16 ounces    (convert)
AuthorJ. N. D. Kelly
Page Count398
Long DescriptionThis is part of a series of modern commentaries based on new English translations made by their respective editors. While adhering strictly to sound scholarship and doctrine, they intend, above all, to bring out the theological and religious message of the New Testament to the contemporary Church.
Similar Items9780801026744: 1 Peter (Baker Exegetical Commentary On The New Testament)
9780800660307: Peter 1 Hermeneia (Hermeneia: A Critical & Historical Commentary on the Bible)
9780800606596: Home for the Homeless
9780788504853: The New American Commentary: 1, 2 Peter, Jude (New American Commentary, 37)
9780664222956: The New Testament World: Insights From Cultural Anthropology 3rd Edition
9780567031693: 1 Peter (New Testament Guides)
9780559144592: Peter 1 Hermeneia (Hermeneia: A Critical & Historical Commentary On The Bible)
9780548032558: Word Biblical Commentary Vol. 46, Pastoral Epistles
9780310492900: 1 Peter (The Niv Application Commentary)
9780070240759: 1 Peter (The Niv Application Commentary)
View 20 more similar items
Created09-24-2012 11:06:13am
Modified04-30-2020 11:43:04pm
Search Googleby EAN or by Title
Query Time0.0171108

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 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.

    INFILE '~/sample_ean_data/sample_ean_product.csv' 
    INTO TABLE ean_product

Finally, lets look at the data that we just imported.


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.