After some additional search, I found the worked link among of lots, which point to 404 pages.
The worked ones are:
Detailed information about these datasets:
Disclaimer: I am the author of below github projects.
Two very good (and complete) sources are:
This has many database formats including all three formats you are inquiring of.
This is a newer continuance of the bible databases, but ...
Regarding your first question, Open Product Data provides guidelines for data importing which suggests using software such as BigDump to handle importing the data.
Now, to answer your second question:
Outpan is my personal project focusing specifically on creating a free database of all barcoded products. The database currently includes more than 18 million ...
looks like possibly same question on stackoverflow:
most results i found recommend using R
looks like these two solutions cost:
You might be able to create an SQL DB by using FERC Enron XERA web application: http://fercenron.omega-caci.com/default.html (user guide).
You'd use the search feature of XERA based on fields, and then export the result to a delimited file, then convert to SQL database for additional queries.
Not exactly SQL but SPARQL:
NL-SPARQL: A Dialog-System Challenge Set for Converting Natural Language to Structured Queries
NL-SPARQL is a data set of natural language (NL) utterances to a conversational system in the movies domain and corresponding queries to Freebase in SPARQL. This dataset was collected via Crowdsourcing as described below.
The data set ...
Here is some information on how to get closer to what you might be looking for.
One well-organized source for information like this is a site called GeoNames.org. GeoNames has a number of APIs as well as downloads ("dumps") which are discussed on their export page.
For your use case, an export seems to make sense. Each country's POIs (points of interest) ...
First you will need to define the schema of your final database and determine how you will map each file to your schema.
Then I recommand using ETL tool (Extract Transform and Load) such as Talend Open Studio (TOS) or Penthao (both are open source solution). Using such tools will allow you to:
automate the process (and not process each file individually)
you can search data.gov, this search returns over 300:
and this search within datasets hosted by data.gov reveals 12:
If it's really simple, you can use the CSV viewer from Github, which has a built-in search tool.
A similar tool is datapipes and for HTML from OKFN Labs. See the demo.
For a more complicated dataset, with more than one table, then another simple option is to export the database as a .SQL file and then let users import it into the SQL database of their ...
If you're looking for some other options, I suggest checking out the Wikipedia page on this topic. You can find it at the link below:
List of online music databases
I have not used them all, but AllMusic is quite good.
Have fun exploring the others and let us know what you think of them. You could even do this by using the "answer your own question&...
The Million Song Dataset has this information as well as other features about the song itself. You can download the entire 300GB file as a flat file, or download a 1% sample.
The full field list can be found at their FAQ, and they have code snippets for working with the data in MatLab, SQL, or other programs.
While your own solution to this dilemma is correct, it might help someone else to explain why your posted solution works, especially if they used another tutorial using another approach to scrape MLB game data, one that doesn't give you the URL of the webpage identifying the location from where game-specific data was scraped.
Initially, I struggled with the ...
If you're looking for completely out of the box solution, datahubs.io or opendata.socrata.com (*) are your best bets.
With all datasets posted on Socrata, you get an embeddable and filterable view (such as https://opendata.socrata.com/d/iu3z-yanc) in addition to an automatically documented API (such as http://dev.socrata.com/foundry/#/opendata.socrata.com/...
You can find homework assignments that are submitted as forks for a MOOC Github repo. In this case, you'll find multiple SQL statements for the same question. The SQL style will be a little biased because all the students are following the same course.
TelerikAcademy - Database Systems Course
Homework assignment for Intro SQL
Then find forks ...
If you know where the end of each query is, then you can add the semi-colon with a command line parsing tool like 'sed'. See here for details about 'sed' on Mac OSX.
You can read about how to use 'sed' to add a semicolon here. To know the exact command, I'd have to know the file details. If each query is on one line, then it's quite straightforward. If ...
I wrote Wik2dict a decade ago to turn MW database dumps into the dict format. It's python code. Could help you figuring out some things.
The best way to convert this xml into mysql is by using mediawiki's xml import functionality.
If you don't have a good reason to import the dump into mysql it's better to avoid it as it's extremely slow with such a large ...
I found some hints for the schema here https://meta.wikimedia.org/wiki/Help:Export#Export_format
To read manually the XML, try using a viewer like:
head -n [numberoflines] dump.xml (gnu/linux terminal)
Here's XML versions of NIV and NRSV: https://github.com/dborza/bible-tools/tree/master/bible-translations (also CEV, ESV, KJV, MKVJ, MSG, NASB, NKJV, NLT).
Generate plain text version of NIV with one verse per line:
wget https://github.com/dborza/bible-tools/raw/master/bible-translations/niv.xml;ruby -rnokogiri -e'Nokogiri.XML(IO.read("niv.xml"))....