1-DAV-202 Data Management 2023/24
Previously 2-INF-185 Data Source Integration

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· Grades from marked homeworks are on the server in file /grades/userid.txt
· Dates of project submission and oral exams:
Early: submit project May 24 9:00am, oral exams May 27 1:00pm (limit 5 students).
Otherwise submit project June 11, 9:00am, oral exams June 18 and 21 (estimated 9:00am-1:00pm, schedule will be published before exam).
Sign up for one the exam days in AIS before June 11.
Remedial exams will take place in the last week of the exam period. Beware, there will not be much time to prepare a better project. Projects should be submitted as homeworks to /submit/project.
· Cloud homework is due on May 20 9:00am.


HWcpp

From MAD
Revision as of 11:03, 12 April 2024 by Teacher (talk | contribs)
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See the lecture

In both tasks, you should implement all functionalities in two versions:

  • Pure Python
  • Python interface with C++ implementation

Then, you should compare the running speed of both implementations.

Task A

You are given a list of documents. Each document consists of multiple words separated by space. You should design and implement an indexing datastructure that allows the following two operations:

  • Add a document to the index (your index should assign it a unique ID)
  • Retrieve a document with the given ID
  • Find all documents that contain the given word

You should ideally implement this as an inverted index, i.e. for each word keep a list of documents containing it.

This is the recommended interface for your datastructure with its example usage:

from typing import List

class DocumentIndex:
  def __init__(self):
    """Initialize what you need here"""
  
  def add_document(self, document:str) -> int:
    """Adds document to index, generates unique id for it"""

  def get_document(self, document_id:int) -> str:
    """Returns document for given ID"""
   
  def search(self, word:str) -> List[int]:
    """Returns list of document IDs containing the given word"""

"""Example usage"""
index = DocumentIndex()

index.add_document("this is document one about frog") # Returns 47
index.add_document("this is document two about dog") # Returns 42
index.get_document(42) # Returns "this is document two about dog"
index.search("dog") # Returns [42]
index.search("cat") # Returns []
index.search("this") # Returns [47, 42] or [42, 47] order of documents is not relevant

Task B

Extend you index so that it support following query:

  • Given list of words (W1, W2, ...) find all documents, which contain all of the words (so each document has to contain all of the word from the query).

You should ideally build on top of functionality from previous task. For each word find documents containing it and then find overlap in the results.

This is the recommended interface for your datastructure with its example usage:

from typing import List

class DocumentIndex:
  def __init__(self):
    """Initialize what you need here"""
  
  def add_document(self, document:str) -> int:
    """Adds document to index, generates unique id for it"""

  def get_document(self, document_id:int) -> str:
    """Returns document for given ID"""
   
  def search(self, word:str) -> List[int]:
    """Returns list of document IDs containing the given word"""

  def multi_search(self, words: List[str]) -> List[int]:
    """Returns list of document IDs that contains all of the words"""

"""Example usage"""
index = DocumentIndex()

index.add_document("this is document one about frog") # Returns 47
index.add_document("this is document two about dog") # Returns 42
index.get_document(42) # Returns "this is document two about dog"
index.search("dog") # Returns [42]
index.search("cat") # Returns []
index.search("this") # Returns [47, 42] or [42, 47] order of documents is not relevant
index.multi_search(["two", "frog"]) # Returns []
index.multi_search(["two", "dog"]) # Returns [42]