7f42043155
this changes the interface to move the readiness check out of the classifier and into the stream object. This massively simplifies the logic connecting these pieces, as classifier is now just a thin wrapper to elastic search. This also adds unit testing for the stream processing through the creation of a fake_gerrit mock class. That lets us run gerrit event interactions in a sane way. It also drops all the unit testing for the classifier which is now largely useless, because all it tests is we can execute a for loop. Change-Id: I1971c121276412e31f01eb5680b9c41fc7e442d3
102 lines
3.4 KiB
Python
102 lines
3.4 KiB
Python
# All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License"); you may
|
|
# not use this file except in compliance with the License. You may obtain
|
|
# a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
|
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
|
# License for the specific language governing permissions and limitations
|
|
# under the License.
|
|
|
|
"""Query builder for pyelasticsearch
|
|
|
|
A set of utility methods to build the kinds of queries that are needed
|
|
by elastic recheck to talk with elastic search.
|
|
"""
|
|
|
|
|
|
def generic(raw_query, facet=None):
|
|
"""Base query builder
|
|
|
|
Takes a raw_query string for elastic search. This is typically the same
|
|
content that you've typed into logstash to get to a unique result.
|
|
|
|
Optionally supports a facet, which is required for certain opperations,
|
|
like ensuring that all the expected log files for a job have been
|
|
uploaded.
|
|
"""
|
|
|
|
# they pyelasticsearch inputs are incredibly structured dictionaries
|
|
# so be it
|
|
query = {
|
|
"sort": {
|
|
"@timestamp": {"order": "desc"}
|
|
},
|
|
"query": {
|
|
"query_string": {
|
|
"query": raw_query
|
|
}
|
|
}
|
|
}
|
|
# if we have a facet, the query gets expanded
|
|
if facet:
|
|
data = dict(field=facet, size=200)
|
|
# yes, elasticsearch is odd, and the way to do multiple facets
|
|
# is to specify the plural key value
|
|
if type(facet) == list:
|
|
data = dict(fields=facet, size=200)
|
|
|
|
query['facets'] = {
|
|
"tag": {
|
|
"terms": data
|
|
}
|
|
}
|
|
|
|
return query
|
|
|
|
|
|
def result_ready(review=None, patch=None, name=None):
|
|
"""A query to determine if we have a failure for a particular patch.
|
|
|
|
This is looking for a particular FAILURE line in the console log, which
|
|
lets us know that we've got results waiting that we need to process.
|
|
"""
|
|
return generic('filename:"console.html" AND '
|
|
'(@message:"[SCP] Copying console log" '
|
|
'OR message:"[SCP] Copying console log") '
|
|
'AND build_status:"FAILURE" '
|
|
'AND build_change:"%s" '
|
|
'AND build_patchset:"%s" '
|
|
'AND build_name:"%s"' %
|
|
(review, patch, name))
|
|
|
|
|
|
def files_ready(review, patch):
|
|
"""A facetted query to ensure all the required files exist.
|
|
|
|
When changes are uploaded to elastic search there is a delay in
|
|
getting all the required log fixes into the system. This query returns
|
|
facets for the failure on the filename, which ensures that we've
|
|
found all the files in the system.
|
|
"""
|
|
return generic('build_status:"FAILURE" '
|
|
'AND build_change:"%s" '
|
|
'AND build_patchset:"%s"' % (review, patch),
|
|
facet='filename')
|
|
|
|
|
|
def single_patch(query, review, patch):
|
|
"""A query for a single patch (review + revision).
|
|
|
|
This is used to narrow down a particular kind of failure found in a
|
|
particular patch iteration.
|
|
"""
|
|
return generic('%s '
|
|
'AND build_change:"%s" '
|
|
'AND build_patchset:"%s"' %
|
|
(query, review, patch))
|