AJAX and JavaScript outshine Java and Oracle in terms of search performance

My team works with a large enterprise application built in Java that interacts with an Oracle SQL database. We utilize JavaScript on the front end and are constantly seeking ways to enhance the performance of our application as its usage grows.

Currently, we are encountering an issue where a Java query is returning 39,000 records, causing a heavy load on the server and leading to browser hang. It's worth noting that the data is relatively static (updating only once a year) and we are considering using an XML map or a similar flat file approach since we know the expected results each time.

Despite our efforts, the query still takes 1.5 - 2 minutes to load, which is unacceptable. We are exploring options to optimize this scenario, including the possibility of leveraging JavaScript (or jQuery) and AJAX for a quicker database connection. We are open to suggestions on how to approach this problem more effectively.

javajavascriptajaxoracleperformance

Answer №1

To determine the cause of the slowness, consider the following factors:

  1. Check if the delay is due to the query execution in the database.
  2. Assess if the network speed is causing the delay in retrieving 39k records.
  3. Evaluate whether the javascript processing of the 39k records after the completion of ajax is contributing to the slowness.

If you can run the query in sqlplus or Toad, this will help exclude the web-tier and network from the equation. If the query is still slow, optimize it by examining indexes.

If optimizing the query does not improve performance, consider prebuilding the query results or creating a materialized view to enhance speed.

Once the query performs well in sqlplus, reintroduce the network element. Run the query from a web browser to analyze any additional overhead.

If the slowness persists, investigate whether the issue lies in the ajax data retrieval or the handling of data on the page (e.g., populating a data grid via javascript).

If the browser is waiting for data, ensure it is fetched only once by setting cache headers in the ajax request or storing results in local storage.

If handling the 39k rows in the browser is causing delays, consider alternative approaches or pagination to mitigate the issue.

Performance problems may arise from various sources, but tuning the query, optimizing indexes, or implementing pre-querying and storage solutions may resolve the issue. Additionally, consider whether fetching 39k rows at once is necessary and implement database-level pagination if possible.

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