1. Elasticsearch
(not just for text search)
Aleck Landgraf
@aleck_landgraf
buildingenergy.com

2. Buildings use a LOT of energy
• Buildings use more energy than any other sector in the US!
• 23% wasted energy*
• $1.2 Trillion wasted
• 40% of GHG wasted(1.1 gigatons annually)**
• What’s the miles per gallon of your office building?
• So how are buildings like mine performing?
• How are my peers’ buildings performing?
*McKinsey & Co: “Unlocking energy efficiency in the US economy”
**equivalent to the entire US fleet of passenger vehicles and lights trucks

3. The Buildings Performance
Database
• With the US DOE, LBNL, we make one of the largest
datasets of building data available (by statistical methods)
• Developer API which enables people to build their own
visualizations and develop fully customized applications
• Expose the DOE Building Energy Performance Taxonomy
through “filters”, the standard for describing buildings
• Provide a decision support tool
• 755k buildings +

4. A Histogram Illustration
/analyze/peers/

5. Why Elasticseach?
• We were choking on data with our previous solution
• It’s not just for text search
• Fast access to a denormalized set of data
• django-haystack integration into our Django stack
• It’s built to scale!
• Aggs!

6. Elasticsearch Aggregations
• stats aggregation
• percentile aggregation
• histogram aggregation
• facet counts

7. stats aggregation
• min, max, std dev, determines bin width
{
"aggs" : {
"eui_stats" : { "stats" : { "field" : "eui" } }
}
}
{
...
!
"aggregations": {
"eui_stats": {
"count": 2194,
"min": 0,
"max": 120,
"avg": 55.8,
"sum": 122425.2
}
}
}

8. percentile aggregation
• quartiles, median (the 0th and 100th quartiles from stats)
{
"aggs" : {
"eui_quartiles" : {
"percentiles" : {
"field" : "eui",
"percents" : [25, 50, 75]
}
}
}
}
{
...
!
"aggregations": {
"eui_quartiles": {
"values" : {
"25.0": 40,
"50.0": 60,
"75.0": 85
}
}
}
}

9. histogram aggregation
• EUI histogram
{
"aggs" : {
“eui_histogram" : {
"histogram" : {
"field" : "eui",
"interval" : 10
}
}
}
}
{
"aggregations": {
“eui_histogram" : {
"buckets": [
{
"key": 0,
"doc_count": 57
},
{
"key": 10,
"doc_count": 93
},
...

10. Elasticsearch Aggregations
• stats aggregation (min, max, std dev, determines bin width)
• percentile aggregation (quartiles, median)
• histogram aggregation (counts per EUI range)

11. Learning curve
• Custom ES backend for django-haystack to add the new ES
features, hope these make it to haystack someday
• Three queries per search to get stats, percentiles, and
histogram. Room for improvement/ES scripts
• Easy to set up in dev and prod, django-haystack keeps ES
and postgres in sync.
• An order of magnitude speed improvement :-)

12. Thanks!
buildingenergy.com
Questions/Comments?
@aleck_landgraf