Implementing Basic NoSQL Queries: Find And Sort Operations

Implementing Basic NoSQL Queries: FIND and SORT Operations

For this assignment you are to write a program to implement the operations required to process and execute NoSQL queries on a preexisting file of data. The data in the file corresponds to a collection in a database. In order to process the query, you will have to parse the query to identify which operations it is requesting, perform the operations on the specified documents and display the results. You must write the code to implement two operations similar to those in MongoDB: a select operation and a sort operation. You cannot run these queries using a database management system, instead you are implementing some of the software yourself for a NoSQL DBS.

You may use the programming language of your choice. You may use any library EXCEPT you must implement the actual FIND and SORT operations yourself. This means you are to implement the project and the selection operations needed for FIND. Also, do not use a built-in sort function. You may implement any sort algorithm you want. Data: The data will be stored in a file named data.txt.

In the data file, each line represents a different document. Each document consists of several fields in the format fieldname: value, separated by spaces, with the field name followed by a colon and a space. All values are integers. Also, generate an ID field named A for each document. The order of fields in each document can vary. All field names are single capital letters from B to W.

Queries are stored in final.txt, and include FIND and SORT operations. The FIND operation retrieves documents based on specified conditions, with optional projection of fields. The sort operation sorts documents based on a specified field and order. Parsing the queries correctly and executing the operations on the data file is essential.

For each query, output the qualifying documents with specified fields in the order they appear in the document, and prefix each set with the query number. If no documents satisfy the query, display nothing. Record the total number of queries processed.

Paper For Above instruction

The implementation of a noSQL-like query processor involves reading structured data, parsing user-defined queries, executing select and sort operations programmatically, and displaying results formatted appropriately. This project demonstrates how fundamental database operations can be replicated through custom code, providing insights into the workings of database management systems (DBMS) without relying on existing database software.

The initial step involves data ingestion: reading data from a text file where each line encodes a document’s fields with their values. Since the data is unstructured in terms of order but structured in terms of syntax, parsing routines must identify each field and its value dynamically. Each document should also be assigned a unique identifier, labeled as 'A', to serve as the document ID, facilitating sorting and referencing.

Following data ingestion, the core challenge lies in interpreting and executing queries. The queries follow a custom syntax resembling MongoDB’s in spirit but differ considerably. For the FIND operation, the parser needs to identify multiple conditional expressions, each containing a field name, a comparison operator, and an integer value. The query may specify multiple conditions, all of which must be satisfied for a document to qualify.

Constructing the evaluation logic involves iterating over each document, testing whether they meet each condition, and considering the absence of fields in documents. If fields are missing from a document, the document automatically disqualifies unless the query conditions are universal or non-restrictive.

Projections specify which fields should be printed. If the projection list contains 'Z', all fields are displayed, including the generated ID 'A'. Otherwise, only specified fields are printed; if a field does not exist in a document, it is ignored in output. The fields in the output should be in the document’s original order, ignoring the order in the projection list.

The SORT operation requires parsing the field designated for sorting and the order—either ascending (1) or descending (-1). Sorting documents involves comparing the specified field across all documents where the field exists, excluding documents lacking the sort key. Sorting can be implemented using any algorithm, such as quicksort or mergesort, deliberately avoiding built-in sort functions to deepen understanding.

To visualize, the implementation must process queries line-by-line, handle errors gracefully, and produce formatted output. When no documents match, output should be empty for that query. When sorting, the documents are displayed in the specified order, sorted based on the chosen field.

Using this structure, the software provides a simplified but functional approximation of parts of a NoSQL database system, illuminating core operational mechanisms such as data retrieval, filtering, and ordering.

References

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