Indexing Performance vs Document Size

Elastic Stack Elasticsearch
1

I see a big difference in indexing throughput between small documents and large documents. Is this expected and why under the below test conditions?

  • Small documents are 1KB, large documents are 10KB to 30KB
  • Observed throughput is 3MB/s vs 20MB/s (not able to beat 4000 documents/sec)
  • Bulk size is 300 documents; There is no improvement in performance beyond this
  • Refresh is disabled (-1)
  • Not analyzing any field
  • Index buffer and translog are sized appropriately
  • Disk storage, no replication, 1 shard
  • No big difference with auto-id

BTW, refresh still happens when index buffer is half full (index buffer must have a ping pong implementation).

I would like to understand what is the per document processing overhead (including per field) and where are the bottlenecks.

2

What ES version? What machine? What operating system? What network interface capacity? What Java VM version? How many clients are indexing?

Each field results in a Lucene index where you can search on. Also, enabled _source and _all contribute to the indexing. If you do not carefully specify your field mapping, you put more load on the document indexing than possibly required.

3
  • ES: 2.3.2, Lucene 5.5.0
  • OS: Ubuntu 14.04.1
  • Java: 8u73
    java version "1.8.0_73"
    Java(TM) SE Runtime Environment (build 1.8.0_73-b02)
    Java HotSpot(TM) 64-Bit Server VM (build 25.73-b02, mixed mode)
  • _all is disabled
  • _source disabled
  • Fields are explicitly mapped
  • Same configs and hardware with only change being document size 1K vs 30K
  • CPU is close to 100%
  • The difference in throughput with size of documents is surprising (3MB/s vs 20MB/s)
4

Maybe the client is challenged? How do you generate the bulk input? What client language/tool? Is the client running on a separate machine?