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I'm new to OLAP and SnappyData. My question is very specific. I want to know where to read further documentation on the SnappyData 'column' query language for OLAP queries. Perhaps it is an industry standard. Perhaps it is SnappyData specific. I don't know.
For clarification, I'm looking at the QuickStart scripts and trying to make sense of the column tables, AIRLINE and the queries in olap_queries.sql. For example, given this query:
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---- Which Airlines Arrive On Schedule? JOIN with reference table ----
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select AVG(ArrDelay) arrivalDelay, description AirlineName, UniqueCarrier carrier
from airline, airlineref
where airline.UniqueCarrier = airlineref.Code
group by UniqueCarrier, description
order by arrivalDelay;
I want to understand the constructs like 'description AirlineName,' . How does the syntax dictate that description is from the join on airlineref? Please, somebody, point me to where I can learn about this syntax.
The description AirlineName is standard column alias specification (where AS is optional) where first one must unambiguously resolve to a table column name in one of the join tables while second one is the alias.
The syntax is the same as Spark SQL syntax. Unfortunately documentation is sparse for it like here or here but it is core SQL-92 compliant for select queries.
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Assuming a table that gives student ID and the courses they took (like English 101, Math 101, etc) and the term term the course was taken in (Fall 2022, Spring 2023, etc) what is the best way to go about finding if students tended to take certain courses together in the same semester?
What's the general term for this analysis?
Possibly similar to R: Which products are bought together more frequently? but that doesn't give the general term for this analysis type.
This type of analysis is called "Association Rule Mining", some packages that you can check out in R are "arules" and "arulesViz" which can be used to perform association rule mining on this type of data.
This medium article is pretty helpful in explaining this concept.
Hope this helps! :)
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I'm studying Java since 8/2020 ans I'm making recipe app for my school project.
I'm using android studio,Java and currently finished making Frontend UI , every layout of my app and connected to FireBase.
on my app I want users to add their food,health data on app and get recipe which fit for their data.
At this point I want to know what tool,program should I use to build my recipe recommendation algorithm and apply it on my app,Firebase.
I searched many Question,post on google and couldn't find what to use.
This is my first complicated app and I don't know much about programming
I'm stuck at this point for 5 days. Can somebody Help me?
The question can have a vast number of answers, and it depends upon your database structure and you to decide, which approach to pick.
You need to search for the data on two bases, i.e. ingredients and health data
One approach could be:
For the ingredients part, this would do the job:
Including an array of tags in each document of a recipe which would list out the ingredients of the recipe by which you can query (array-contains)
And for the health data part, I'm not quite sure what you mean by filtering based on health but let's say; you are going to search for the recipes based on the calories the user needs in a day. So after calculating the calories required in a day, it would be like:
Including a field of totalCalories in each document of a recipe which would tell the total calories in the recipe by which you can query (whereEqualTo or whereLessThan)
I suggest you read the Firebase documentation for executing the queries to get to know about all the possible ways.
Perform simple and compound queries in Cloud Firestore
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while reading the sqlite change log I came across this statement
2012-03-20 (3.7.11)
...
Queries of the form: "SELECT max(x), y FROM table" returns the value of y on the same row that contains the maximum x value.
...
I found the commits that implement this feature, in the hope of finding documentation but no luck.
I find myself using this feature all the time and wondering:
Is there documentation of this feature?
When can I rely on it applying?
Are there gotchas in using it?
Are there similar queries that it doesn't work for?
You have quoted the entire documentation of this feature.
This does not work if there are multiple occurrences of max()/min() (you cannot choose which is the controlling one), or if the max() is not actually computed because an outer query ignores it.
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I have been trying to find a program that can extract information from unstructured text(news articles, books, etc).
My eventual goal is to create a program that can take regular sentences and cache it in a database much like google does but without all its duplicate information.
lets take the NLTK example: "At eight o'clock on Thursday morning Arthur didn't feel very good."
the things that i would want extracted would be:
time: 8:00pm
date: thursday
person: Arthur
action: didn't feel good
is there a program that can do this?
i have tried using NLTK but i cant seem to find any good way to accomplish extracting the information.
This problem is called Fine grained entity recognition. No, There are no tools (except for research works) that can add such semantics.
To start with, you can recognise Person and Time with appropriate models using Entity Recogniser.
You can recognise the actions from sentence parsing as suggested by #Junuxx.
Also give Wikify a try.
Thank you.
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I want to make a Vocabulary Trainer and I was thinking about the best way to do it. First I searched some translation APIs to use, to avoid having to build my own dictionary, but I found that most of them are paid and some are free but have limitations.
So, I think the best way is to make my own dictionary, which also allow me to work offline, but I wonder if there is any free database of English-Spanish words to avoid starting from scratch.
Do you know any?
Thanks a lot!
You could try http://www.omegawiki.org/ as they claim this:
The aim of our project is to create a dictionary of all words of all languages, including lexical, terminological and ontological information. Our data is available in a relational database, as a result it is possible to use the data for many purposes.