Image
EAN-139786302430912   EAN-13 barcode 9786302430912
Product NameMeatballs, Part II [VHS]
CategoryElectronics / Photography: A/V Media: Movie
Amazon.comA Buy on Amazon ~ 6302430917
Price New17.78 US Dollars    (curriencies)
Price Used3.32 US Dollars    (curriencies)
RatingPG - Parental Guidance Suggested
IMDbIMDb Link
Run Time87 minutes
CastArchie Hahn, Hamilton Camp, John Mengatti, Kim Richards, Richard Mulligan
DirectorKen Wiederhorn
GenreCOMEDY
Run Time87 minutes
BindingVHS Tape
Release Year1984
FormatClosed-captioned, Color, NTSC
Run Time87 minutes
Long DescriptionIn this sequel to the teenage summer camp comedy Meatballs, the usual '80s misfits come together in a series of comic misadventures, and then band together to save their beloved Camp Sasquatch. John Mengatti stars as Flash, a juvenile delinquent who's given the choice of reform school or serving as a camp counselor at Camp Sasquatch, where he has the opportunity to pursue fellow counselor Kim Richards (Escape to Witch Mountain). Among the various oddball campers is a space alien nicknamed "Meathead" - we're guessing your weird summer camp experience was never like this!! Great eighties favorites John Larroquette, Richard Mulligan, Misty Rowe, Jason Hervey, and Paul Reubens (aka Pee-wee Herman) star.
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0031398149309: Meatballs
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Created02-28-2013 10:39:39am
Modified04-27-2018 3:10:23am
MD5ca4023f493e2a472a91d2926e75d734b
SHA256df6b1835bc973f6bf8ee1301a004c92f65a1c5b959be8d2fdf4f8a6d08da3088
Search Googleby EAN or by Title
Query Time0.0127542

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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