**
Quick summary: C++ app loading data from SQL server using using OTL4, writing to Mongo using mongocxx bulk_write, the strings seem to getting mangled somehow so they don't work in the aggregation pipeline (but appear fine otherwise).
**
I have a simple Mongo collection which doesn't seem to behave as expected with an aggregation pipeline when I'm projecting multiple fields. It's a trivial document, no nesting, fields are just doubles and strings.
First 2 queries work as expected:
> db.TemporaryData.aggregate( [ { $project : { ParametersId:1 } } ] )
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "ParametersId" : 526988617 }
> db.TemporaryData.aggregate( [ { $project : { Col1:1 } } ] )
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "Col1" : 575 }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "Col1" : 579 }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "Col1" : 616 }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "Col1" : 617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "Col1" : 622 }
But then combining doesn't return both the fields as expected.
> db.TemporaryData.aggregate( [ { $project : { ParametersId:1, Col1:1 } } ] )
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "ParametersId" : 526988617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "ParametersId" : 526988617 }
It seems to be specific to the ParametersId field, for instance if I choose 2 other fields it's OK.
> db.TemporaryData.aggregate( [ { $project : { Col1:1, Col2:1 } } ] )
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "Col1" : 575, "Col2" : "1101-2" }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "Col1" : 579, "Col2" : "1103-2" }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "Col1" : 616, "Col2" : "1300-3" }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "Col1" : 617, "Col2" : "1300-3" }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "Col1" : 622, "Col2" : "1400-3" }
For some reason when I include ParametersId field, all hell breaks loose in the pipeline:
> db.TemporaryData.aggregate( [ { $project : { ParametersId:1, Col2:1, Col1:1, Col3:1 } } ] )
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "ParametersId" : 526988617, "Col1" : 575 }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "ParametersId" : 526988617, "Col1" : 579 }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "ParametersId" : 526988617, "Col1" : 616 }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "ParametersId" : 526988617, "Col1" : 617 }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "ParametersId" : 526988617, "Col1" : 622 }
DB version and the data:
> db.version()
4.0.2
> db.TemporaryData.find()
{ "_id" : ObjectId("5c28f751a531251fd0007c72"), "CellId" : 998909269, "ParametersId" : 526988617, "Order" : 1, "Col1" : 575, "Col2" : "1101-2", "Col3" : "CHF" }
{ "_id" : ObjectId("5c28f751a531251fd0007c73"), "CellId" : 998909269, "ParametersId" : 526988617, "Order" : 1, "Col1" : 579, "Col2" : "1103-2", "Col3" : "CHF" }
{ "_id" : ObjectId("5c28f751a531251fd0007c74"), "CellId" : 998909269, "ParametersId" : 526988617, "Order" : 1, "Col1" : 616, "Col2" : "1300-3", "Col3" : "CHF" }
{ "_id" : ObjectId("5c28f751a531251fd0007c75"), "CellId" : 998909269, "ParametersId" : 526988617, "Order" : 36, "Col1" : 617, "Col2" : "1300-3", "Col3" : "CHF" }
{ "_id" : ObjectId("5c28f751a531251fd0007c76"), "CellId" : 998909269, "ParametersId" : 526988617, "Order" : 1, "Col1" : 622, "Col2" : "1400-3", "Col3" : "CHF" }
Update: enquoting the field names makes no difference. I'm typing all the above in the mongo.exe command line, but I see the same behavior in my C++ application with a slightly more complex pipeline (projecting all fields to guarantee order).
This same app is actually creating the data in the first place - does anyone know anything which can go wrong? All using the mongocxx lib.
** update **
Turns out there's something going wrong with my handling of strings. Without the string fields in the data, it's all fine. So I've knackered my strings, somehow, even though they look and behave correctly in other ways they don't play nice with the aggregation pipeline. I'm using mongocxx::collection.bulk_write to write standard std::strings which are being loaded from sql server through the OTL4 header. In-between there's a strncpy_s when they get stored internally. I can't seem to create a simple reproducible example.
Just to be safe that there is no conflict with anything else, try using the projection with a strict formatted json: (add quotes to keys)
db.TemporaryData.aggregate( [ { $project : { "ParametersId":1, "Col1":1 } } ] )
Finally found the issue was corrupt documents, which because I was using bulk_write for the insert were getting into the database but causing this strange behavior. I switched to using insert_many, which threw up the document was corrupt, and then I could track down the bug.
The docs were corrupt because I was writing the same field-value data multiple times, which seems to be break the bsoncxx::builder::stream::document I was using to construct them.
Related
I'm trying to filter a query with term and range along with query-string. filter(range) and query string works but not filter(term). am i doing something wrong?
es = Elasticsearch([{'host': '192.168.121.121', 'port': 9200}])
index = Index("filebeat-*",using=es)
search = index.search()
searchStr = "OutOfMemoryError"
search = search.query("query_string", query=searchStr)
search = search.filter('range' , **{'#timestamp': {'gte': 1589399137000 , 'lt': 1589399377000, 'format' : 'epoch_millis'}})
search = search.filter('term' , **{'can.deployment': 'can-*' })
response = search.execute(ignore_cache=True)
print(response.hits.total)
print(response.hits.hits._source.can.deployment)
json:
filter-term - ['hits']['hits']['_source']['can']['deployment']
filter-range- ['hits']['hits']['_source']['#timestamp']
{
"hits" : {
"total" : 138351328,
"max_score" : 6.5700893,
"hits" : [
{
"_index" : "filebeat-6.1.2-2020.05.13",
"_type" : "doc",
"_score" : 2.0166037,
"_source" : {
"#timestamp" : "2020-05-13T01:14:03.354Z",
"source" : "/var/log/gw_rest/gw_rest.log",
"message" : "[2020-05-13 01:14:03.354] WARN can_gw_rest [EventLoopGroup-3-2]: An exceptionCaught() event was fired.OutOfMemoryError,
"fileset" : {...},
"can" : {
"level" : "WARN",
>>>>>>>> "message" : "An exceptionCaught() event was fired- OutOfMemoryError,
"timestamp" : "2020-05-13 01:14:03.354",
>>>>>>>> "deployment" : "can-6b721b93965b-w3we4-4074-9903"
}
}
}
]
}
}
I actually didn't need a filter(term). this worked:
dIds=response['hits']['hits'][1]['_source']['can']['deployment']
print(dIds)
#loop through the response
for i in response['hits']['hits']:
id = i['_source']['can']['deployment']
print(id)
I have the following DynamoDB mapping template, to update an existing DynamoDB item:
{
"version" : "2017-02-28",
"operation" : "UpdateItem",
"key" : {
"id": $util.dynamodb.toDynamoDBJson($ctx.args.application.id),
"tenant": $util.dynamodb.toDynamoDBJson($ctx.identity.claims['http://domain/tenant'])
},
"update" : {
"expression" : "SET #sourceUrl = :sourceUrl, #sourceCredential = :sourceCredential, #instanceSize = :instanceSize, #users = :users",
"expressionNames" : {
"#sourceUrl" : "sourceUrl",
"#sourceCredential" : "sourceCredential",
"#instanceSize" : "instanceSize",
"#users" : "users"
},
"expressionValues" : {
":sourceUrl" : $util.dynamodb.toDynamoDbJson($ctx.args.application.sourceUrl),
":sourceCredential" : $util.dynamodb.toDynamoDbJson($ctx.args.application.sourceCredential),
":instanceSize" : $util.dynamodb.toDynamoDbJson($ctx.args.application.instanceSize),
":users" : $util.dynamodb.toDynamoDbJson($ctx.args.application.users)
}
},
"condition" : {
"expression" : "attribute_exists(#id) AND attribute_exists(#tenant)",
"expressionNames" : {
"#id" : "id",
"#tenant" : "tenant"
}
}
}
But I'm getting the following error:
message: "Unable to parse the JSON document: 'Unrecognized token '$util': was expecting ('true', 'false' or 'null')↵ at [Source: (String)"{↵ "version" : "2017-02-28",↵ "operation" : "UpdateItem",↵ "key" : {↵ "id": {"S":"abc-123"},↵ "tenant": {"S":"test"}↵ },↵ "update" : {↵ "expression" : "SET #sourceUrl = :sourceUrl, #sourceCredential = :sourceCredential, #instanceSize = :instanceSize, #users = :users",↵ "expressionNames" : {↵ "#sourceUrl" : "sourceUrl",↵ "#sourceCredential" : "sourceCredential",↵ "#instanceSize" : "instanceSize",↵ "#users" : "users"↵ }"[truncated 400 chars]; line: 17, column: 29]'"
I've tried removing parts, and it seems to be related to the expressionValues, but I can't see anything wrong with the syntax.
Seems like you misspelled the toDynamoDBJson method
Replace
$util.dynamodb.toDynamoDbJson($ctx.args.application.sourceUrl)
with
$util.dynamodb.toDynamoDBJson($ctx.args.application.sourceUrl)
Note the uppercase B in toDynamoDBJson.
I have the following query:
{
"query" : {
"bool" : {
"must" : [
{
"query_string" : {
"query" : "dog cat",
"analyzer" : "standard",
"default_operator" : "AND",
"fields" : ["title", "content"]
}
},
{
"range" : {
"dateCreate" : {
"gte" : "2018-07-01T00:00:00+0200",
"lte" : "2018-07-31T23:59:59+0200"
}
}
},
{
"regexp" : {
"articleIds" : {
"value" : ".*?(2561|30|540).*?",
"boost" : 1
}
}
}
]
}
}
}
The fields title, content and articleIds are of type text, dateCreate is of type date. The articleIds field contains some IDs (comma-separated).
Ok, what happens now? I execute the query an get two results: Both documents contain the words "dog" and "cat" in the title or in the content. So far it's correct.
But the second result has the number 3507 in the articleIds field which doesn't match to my query. It seems that the regexp is ignored because title and content already match. What is wrong here?
And here's the document that should not match my query but does:
{
"_index" : "example",
"_type" : "doc",
"_id" : "3007780",
"_score" : 21.223656,
"_source" : {
"dateCreate" : "2018-07-13T16:54:00+0200",
"title" : "",
"content" : "Its raining cats and dogs.",
"articleIds" : "3507"
}
}
And what I'm expecting is that this document should not be in the results because it contains 3507 which is not part of my query...
var allCollections = db.getCollectionNames();
for (var i = 0; i < allCollections.length; ++i) {
var collectioname = allCollections[i];
if (collectioname === 'system.indexes')
continue;
db.runCommand(
{ "mapreduce" : collectioname, "map" : function()
{
for (var key in this) {
emit(key, null);
}
}, "reduce" : function(key, stuff) {
return null;
}, "out":mongo_test + "_keys"
}) }
output
{ "_id" : "_id", "value" : null }
{ "_id" : "collection_name", "value" : null }
{ "_id" : "database", "value" : null }
{ "_id" : "host", "value" : null }
{ "_id" : "port", "value" : null }
{ "_id" : "cardid", "value" : null }
{ "_id" : "ccard", "value" : null }
{ "_id" : "creditcardnum", "value" : null }
{ "_id" : "date", "value" : null }
{ "_id" : "value", "value" : null }
I want collectionname in the "value" field instead of null .
I'm using django-haystack and ElasticSearch to index Stores.
Until now, each store had one lat,long coordinate pair; we had to change this to represent the fact that one store can deliver products to very different regions (disjunct) I've added up to ten locations (lat,long pairs) to them.
When using one location field everything was working fine and I got right results. Now, with multiple location fields, I can't get any results, not even the previuos one, for the same user and store coordinates.
My Index is as following:
class StoreIndex(indexes.SearchIndex,indexes.Indexable):
text = indexes.CharField(document=True, use_template=True,
template_name='search/indexes/store/store_text.txt')
location0 = indexes.LocationField()
location1 = indexes.LocationField()
location2 = indexes.LocationField()
location3 = indexes.LocationField()
location4 = indexes.LocationField()
location5 = indexes.LocationField()
location6 = indexes.LocationField()
location7 = indexes.LocationField()
location8 = indexes.LocationField()
location9 = indexes.LocationField()
def get_model(self):
return Store
def prepare_location0(self, obj):
# If you're just storing the floats...
return "%s,%s" % (obj.latitude, obj.longitude)
# ..... up to prepare_location9
def prepare_location9(self, obj):
# If you're just storing the floats...
return "%s,%s" % (obj.latitude_9, obj.longitude_9)
Is this the correct way to build my index?
From elasticsearch I get this mapping information:
curl -XGET http://localhost:9200/stores/_mapping?pretty=True
{
"stores" : {
"modelresult" : {
"properties" : {
"django_id" : {
"type" : "string"
},
"location0" : {
"type" : "geo_point",
"store" : "yes"
},
"location1" : {
"type" : "geo_point",
"store" : "yes"
},
"location2" : {
"type" : "geo_point",
"store" : "yes"
},
"location3" : {
"type" : "geo_point",
"store" : "yes"
},
"location4" : {
"type" : "geo_point",
"store" : "yes"
},
"location5" : {
"type" : "geo_point",
"store" : "yes"
},
"location6" : {
"type" : "geo_point",
"store" : "yes"
},
"location7" : {
"type" : "geo_point",
"store" : "yes"
},
"location8" : {
"type" : "geo_point",
"store" : "yes"
},
"location9" : {
"type" : "geo_point",
"store" : "yes"
},
"text" : {
"type" : "string",
"analyzer" : "snowball",
"store" : "yes",
"term_vector" : "with_positions_offsets"
}
}
}
}
}
Then, I try to query this way:
sqs0 = SearchQuerySet().dwithin('location0', usuario, max_dist).distance('location0',usuario).using('stores')
where:
usuario is a Point instance representing the user trying to find stores near his position and
max_dist is a D instance.
If I query directly, using curl I got no results, too.
Here is the result of quering using curl with multiple location fields:
$ curl -XGET http://localhost:9200/stores/modelresult/_search?pretty=true -d '{ "query" : { "match_all": {} }, "filter" : {"geo_distance" : { "distance" : "6km", "location0" : { "lat" : -23.5, "lon" : -46.6 } } } } '
{
"took" : 1,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 0,
"max_score" : null,
"hits" : [ ]
}
}
If comment out the fields location1-9 from the StoreIndex class everything works fine, but if I leave them to get multiple location points, I get no results for the same query (user position). This happens for the same query, in django as directly, using curl. That is, if I have only one location (say location0), both queries returns correct results. With more locations (location0-9), both queries didn't give any results.
Here's the results of quering directly using curl with only one location field:
$ curl -XGET http://localhost:9200/stores/modelresult/_search?pretty=true -d '{ "query" : { "match_all": {} }, "filter" : {"geo_distance" : { "distance" : "6km", "location0" : { "lat" : -23.5, "lon" : -46.6 } } } } '
{
"took" : 3,
"timed_out" : false,
"_shards" : {
"total" : 5,
"successful" : 5,
"failed" : 0
},
"hits" : {
"total" : 9,
"max_score" : 1.0,
"hits" : [ {
"_index" : "stores",
"_type" : "modelresult",
"_id" : "store.store.110",
"_score" : 1.0, "_source" : {"django_ct": "store.store", "text": "RESULT OF THE SEARCH \n\n", "django_id": "110", "id": "store.store.110", "location0": "-23.4487554,-46.58912"}
},
lot's of results here
]
}
}
Of course, I rebuild_index after any change in StoreIndex.
Any help on how to get multiple location fields working with elasticsearch and django?
PS.: I've cross posted this question on Django-Haystack and ElasticSearch Google Groups.
https://groups.google.com/d/topic/elasticsearch/85fg7vdCBBU/discussion
https://groups.google.com/d/topic/django-haystack/m2A3_SF8-ls/discussion
Thanks in advance
Mário