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https://issues.apache.org/jira/browse/DRILL-8491?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Piyush Shama updated DRILL-8491:
--------------------------------
Description:
{*}Title{*}: Inefficient Query Translation and Underutilised Functions in SQL
to MongoDB Conversion Using Apache Drill
{*}Description{*}: We have been experiencing significant performance issues
when using Apache Drill to convert SQL queries for use with MongoDB. It appears
that the SQL to MongoDB query translation process is not optimally executed,
leading to inefficient query operations and slow response times.
{*}Details{*}:
# {*}Inefficient Query Translation{*}:
** The translation of SQL queries into MongoDB-specific queries by Apache
Drill seems sub optimal. This inefficiency is particularly noticeable with
complex queries, where the expected execution plan does not align with
MongoDB's capabilities, resulting in slower query performance.
# {*}Underutilization of MongoDB Capabilities{*}:
** Several MongoDB functionalities are not being fully utilised in the
translation process:
*** {*}Aggregation Operations{*}: Functions like {{{}SUM(){}}}, {{{}AVG(){}}},
{{{}MIN(){}}}, and {{MAX()}} are either poorly translated or not utilised,
leading to potential performance degradation.
*** {*}Date Handling{*}: Extraction of date components (e.g., day from an ISO
date) within queries is not handled efficiently, forcing additional processing
overhead or client-side computations.
*** {*}Count Queries{*}: Simple count operations are not optimised, possibly
translating into more complex query forms than necessary.
{*}Impact{*}: The current issues significantly affect the performance and
scalability of applications relying on Apache Drill for interacting with
MongoDB, particularly in data-heavy environments.
{*}Expected Behaviour{*}:
* Queries translated from SQL to MongoDB should utilise MongoDB's native query
capabilities more effectively, ensuring that operations such as aggregations,
date extractions, and counts are executed in the most efficient manner possible.
* The translation engine should optimise the query structure to leverage
MongoDB's strengths, particularly in handling large datasets.
{*}Steps to Reproduce{*}:
# Set up Apache Drill with a MongoDB data source.
# Execute complex SQL queries involving aggregation, date extraction, and
count operations.
# Observe the generated MongoDB queries and resulting performance.
> MongoDB | Queries Conversion optimisation & using various mongoDB features
> --------------------------------------------------------------------------
>
> Key: DRILL-8491
> URL: https://issues.apache.org/jira/browse/DRILL-8491
> Project: Apache Drill
> Issue Type: Improvement
> Reporter: Piyush Shama
> Priority: Major
>
> {*}Title{*}: Inefficient Query Translation and Underutilised Functions in SQL
> to MongoDB Conversion Using Apache Drill
> {*}Description{*}: We have been experiencing significant performance issues
> when using Apache Drill to convert SQL queries for use with MongoDB. It
> appears that the SQL to MongoDB query translation process is not optimally
> executed, leading to inefficient query operations and slow response times.
> {*}Details{*}:
> # {*}Inefficient Query Translation{*}:
> ** The translation of SQL queries into MongoDB-specific queries by Apache
> Drill seems sub optimal. This inefficiency is particularly noticeable with
> complex queries, where the expected execution plan does not align with
> MongoDB's capabilities, resulting in slower query performance.
> # {*}Underutilization of MongoDB Capabilities{*}:
> ** Several MongoDB functionalities are not being fully utilised in the
> translation process:
> *** {*}Aggregation Operations{*}: Functions like {{{}SUM(){}}},
> {{{}AVG(){}}}, {{{}MIN(){}}}, and {{MAX()}} are either poorly translated or
> not utilised, leading to potential performance degradation.
> *** {*}Date Handling{*}: Extraction of date components (e.g., day from an
> ISO date) within queries is not handled efficiently, forcing additional
> processing overhead or client-side computations.
> *** {*}Count Queries{*}: Simple count operations are not optimised, possibly
> translating into more complex query forms than necessary.
> {*}Impact{*}: The current issues significantly affect the performance and
> scalability of applications relying on Apache Drill for interacting with
> MongoDB, particularly in data-heavy environments.
> {*}Expected Behaviour{*}:
> * Queries translated from SQL to MongoDB should utilise MongoDB's native
> query capabilities more effectively, ensuring that operations such as
> aggregations, date extractions, and counts are executed in the most efficient
> manner possible.
> * The translation engine should optimise the query structure to leverage
> MongoDB's strengths, particularly in handling large datasets.
> {*}Steps to Reproduce{*}:
> # Set up Apache Drill with a MongoDB data source.
> # Execute complex SQL queries involving aggregation, date extraction, and
> count operations.
> # Observe the generated MongoDB queries and resulting performance.
>
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