elasticsearch/elasticsearch — Issue #1418: First indexing fails when indexing a type with an attachment field mapped using a dynamic template
Author: joelabrahamsson
Created: 2011-10-22 18:08:57+00:00
State: open

When mapping fields that match a certain pattern as attachments using dynamic templates indexing will crash the first time a type is indexed with such a field. That is, for each type with such a field, the first request will fail. Subsequent indexing operations work fine.

I have yet to test this with versions higher than 0.17.6 but I've not seen any fix for it in the release notes so while I'm experiencing this with 0.17.6 I'm guessing it's the same in later versions.

To replicate the following steps can be performed. The POST will fail with {"error":"NullPointerException[null]","status":500}

curl -XPUT 'http://localhost:9200/myindex/' -d
'{
"mappings": {
"_default_": {
"dynamic_templates": [
{
"attachment_template": {
"match": "*$$attachment",
"mapping": {
"type": "attachment"
}
}
}
]
}
}
}'

curl -XPOST 'http://localhost:9200/myindex/mytype' -d
'{
"Attachment$$attachment": "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}'