GemFire - Pagination Strategies for Large Data Sets

Products

• VMware Tanzu Data Intelligence
• VMware Tanzu Data Suite
• VMware Tanzu Data Suite
• VMware Tanzu Gemfire
• VMware Tanzu Greenplum / Gemfire

Issue/Introduction

Applications interacting with GemFire often need to retrieve large volumes of data from regions using Java-based services. In cases where a region contains millions of entries, clients may require paginated access to the data while ensuring:

• Low response latency

• Minimal load on GemFire servers

• No key management on the client side

• Ability to request data using only a page number

This article describes how pagination can be implemented in GemFire and outlines recommended best practices.

Cause

GemFire does not provide a built-in server-side pagination mechanism similar to relational databases.

Key limitations include:

• Region.getAll() requires keys to be known in advance

• OQL does not natively support cursor-based pagination

• Fetching all region values in a single operation can increase heap usage, network traffic, and latency

As a result, pagination must be implemented at the application or service layer using supported GemFire APIs.

Resolution

The following techniques are recommended to implement pagination efficiently, depending on the access pattern and query requirements.

• We can page Search results using GemFire Search : Please refer https://techdocs.broadcom.com/us/en/vmware-tanzu/data-solutions/tanzu-gemfire-search/1-2/gf-search/search_landing.html
• Page Query results using OQL

  • Get All Keys with a OQL, ex: select key from account.entries where value.name = $1

  • Split keys into a list of list of keys

  • Get list of keys based on page index ex: var pagedKeys = list.get(pageIndex)

  • Get region values with batched keys ex: var pageValues = region.getAll(pagedKeys)