# Huge difference in index size when bulk indexing geoshapes across ES versions

**URL:** <https://discuss.elastic.co/t/huge-difference-in-index-size-when-bulk-indexing-geoshapes-across-es-versions/97137>\
**Category:** Elasticsearch\
**Created:** [August 15, 2017, 5:06pm UTC](https://discuss.elastic.co/t/huge-difference-in-index-size-when-bulk-indexing-geoshapes-across-es-versions/97137 "2017-08-15T17:06:39Z")\
**Posts on this page:** 1\
**Showing post:** 4

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**Author:** ![Mark\_Harwood](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mark_harwood/32/10538_2.png) [@Mark\_Harwood](https://discuss.elastic.co/u/Mark_Harwood)\
**Post date:** [September 7, 2017, 12:03pm UTC](https://discuss.elastic.co/t/huge-difference-in-index-size-when-bulk-indexing-geoshapes-across-es-versions/97137/4 "2017-09-07T12:03:51Z")

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> [@sbocconi](#):
>
> Size on the cluster is 7.4mb, on the single node is 4.8gb (using precision 10m

7.1 mb looks to be the original json data size and the explosion in size can be thought of as a similar cost to converting a vector graphic into a raster one. While the vector graphic may describe a diagonal line using only 2 coordinates an equivalent high-resolution, massive scale raster format would be much bigger. Like the pixels in an image, entries in the index represent the cells in a space of your own sizing choice.

This discussion has more of this detail:

> <https://github.com/elastic/elasticsearch/issues/25833>
>
> We have been discussing this for a while and it seems to be that quadtree(s) are… much faster to be indexed. Also, most people don't realize that setting \`precision\` will then default \`distance\_error\_pct\` to zero, also causing the indexing times of geo shapes to be very slow.
> 
> My proposal here is to:
> 
> 1. Change the default \`tree\` to \`quadtree\` .
> 2. Default distance\_error\_pct to \`0.001\` when \`precision\` is set.
> 
> CC @nknize

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