With PyMongo, group by one key seems to be ok:
results = collection.group(key={"scan_status":0}, condition={'date': {'$gte': startdate}}, initial={"count": 0}, reduce=reducer)
results:
{u'count': 215339.0, u'scan_status': u'PENDING'} {u'count': 617263.0, u'scan_status': u'DONE'}
but when I try to do group by multiple keys I get an exception:
results = collection.group(key={"scan_status":0,"date":0}, condition={'date': {'$gte': startdate}}, initial={"count": 0}, reduce=reducer)
How can I do group by multiple fields correctly?
If you are trying to count over two keys then while it is possible using .group() your better option is via .aggregate().
This uses "native code operators" and not the JavaScript interpreted code as required by .group() to do the same basic "grouping" action as you are trying to achieve.
Particularly here is the $group pipeline operator:
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": "$date"
},
"count": { "$sum": 1 }
}}
])
In fact you probably want something that reduces the "date" into a distinct period. As in:
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": {
"year": { "$year": "$date" },
"month": { "$month" "$date" },
"day": { "$dayOfMonth": "$date" }
}
},
"count": { "$sum": 1 }
}}
])
Using the Date Aggregation Operators as shown here.
Or perhaps with basic "date math":
import datetime
from datetime import date
result = collection.aggregate([
# Matchn the documents possible
{ "$match": { "date": { "$gte": startdate } } },
# Group the documents and "count" via $sum on the values
# use "epoch" "1970-01-01" as a base to convert to integer
{ "$group": {
"_id": {
"scan_status": "$scan_status",
"date": {
"$subtract": [
{ "$subtract": [ "$date", date.fromtimestamp(0) ] },
{ "$mod": [
{ "$subtract": [ "$date", date.fromtimestamp(0) ] },
1000 * 60 * 60 * 24
]}
]
}
},
"count": { "$sum": 1 }
}}
])
Which will return integer values from "epoch" time instead of a compisite value object.
But all of these options are better than .group() as they use native coded routines and perform their actions much faster than the JavaScript code you need to supply otherwise.
Related
I was wondering if it was possible to somehow use the $match operator within the $sum function for aggregation.
{ "$unwind": "$info.avatarInfoList" },
{ "$unwind": "$info.avatarInfoList.equipList" },
{ "$unwind": "$info.avatarInfoList.equipList.flat.reliquarySubstats" },
{
"$project": {
"name" : "$name",
"character" : "$info.avatarInfoList.avatarId",
"artifact" : "$info.avatarInfoList.equipList.itemId",
"statValue" : {
"$sum": [
{"$match" : { "$info.avatarInfoList.equipList.flat.reliquarySubstats.appendPropId" : "FIGHT_PROP_CRITICAL_HURT" } },
{"$multiply": [2, {"$match" : { "$info.avatarInfoList.equipList.flat.reliquarySubstats.appendPropId" : "FIGHT_PROP_CRITICAL" } }]}
]
},
}
},
{ "$sort": { "statValue": -1 }},
{ '$limit' : 30 }
]).to_list(length=None)
print(data)
I want to be able to use the value of the $sum operator within the project fields somehow, I just don't really understand what the right approach would be for this.
Sample Input (may be too long):
https://www.toptal.com/developers/hastebin/ixamekaxoq.json
Sample Output:
( 2 * FIGHT_PROP_CRITICAL ) + FIGHT_PROP_CRITICAL_HURT sorted from highest to lowest for each item.
{name: hat, character: Slayer, artifact: 13, statValue : 25.6}
There are still a few ambiguities about how you want to aggregate your data, but using the full document from your link, here's one way to produce the output you want.
N.B.: Weapons in the "equipList" don't have "reliquarySubstats" so they show a "statValue" of null in the output.
db.collection.aggregate([
{"$unwind": "$info.avatarInfoList"},
{"$unwind": "$info.avatarInfoList.equipList"},
{
"$project": {
"_id": 0,
"name": 1,
"character": "$info.avatarInfoList.avatarId",
"artifact": "$info.avatarInfoList.equipList.itemId",
"statValue": {
"$reduce": {
"input": "$info.avatarInfoList.equipList.flat.reliquarySubstats",
"initialValue": 0,
"in": {
"$switch": {
"branches": [
{
"case": {"$eq": ["$$this.appendPropId", "FIGHT_PROP_CRITICAL"]},
"then": {
"$add": [
"$$value",
{"$multiply": [2, "$$this.statValue"]}
]
}
},
{
"case": {"$eq": ["$$this.appendPropId", "FIGHT_PROP_CRITICAL_HURT"]},
"then": {"$add": ["$$value", "$$this.statValue"]}
}
],
"default": "$$value"
}
}
}
}
}
},
{"$sort": {"statValue": -1}}
])
Try it on mongoplayground.net.
It's not quite clear what you want to achieve, but as mentioned you want to be using $cond here.
like so:
{
"$project": {
"statValue": {
"$sum": [
{
$cond: [
{ // if this condition is true (prop id = prop critical hurt )
$eq: [
"$info.avatarInfoList.equipList.flat.reliquarySubstats.appendPropId",
"FIGHT_PROP_CRITICAL_HURT"
]
},
{ // then use this value for the "$sum"
"$multiply": [
2,
"$info.avatarInfoList.equipList.flat.reliquarySubstats.statValue"
]
},
0 // otherwise use this value for the sum.
]
}
]
}
}
Mongo Playground
I have a database collection that has objects like this:
{
"_id": ObjectId("something"),
"name_lower": "total",
"name": "Total",
"mounts": [
[
"mount1",
"instance1"
],
[
"mount2",
"instance1"
],
[
"mount1",
"instance2"
],
[
"mount2",
"instance2"
]
]
}
Say I want to remove every mount that has the instance instance2, How would I go about doing that? I have been searching for quite a while.
You can do something like this
[
{
$unwind: "$mounts"
},
{
$match: {
"mounts": {
$ne: "instance2"
}
}
},
{
$group: {
_id: "$_id",
name: {
$first: "$name"
},
mounts: {
$push: "$mounts"
}
}
}
]
Working Mongo playground
This answer is based on #varman answer but more pythonic and efficient.
The first stage should be a $match condition to filter out documents that don't need to be updated.
Since the mounts key consists of a nested array, we have to $unwind it, so that we can remove array elements that need to be removed.
We have to apply the $match condition again to filter out the element that has to be removed.
Finally, we have to $group the pipeline by _id key, so that the documents which got $unwind in the previous stage will be groupped into a single document.
from pymongo import MongoClient
client = MongoClient("<URI-String>")
col = client["<DB-Name"]["<Collection-Name>"]
count = 0
for cursor in col.aggregate([
{
"$match": {
"mounts": {"$ne": "instance2"}
}
},
{
"$unwind": "$mounts"
},
{
"$match": {
"mounts": {"$ne": "instance2"}
}
},
{
"$group": {
"_id": "$_id",
"newMounts": {
"$push": "$mounts"
}
}
},
]):
# print(cursor)
col.update_one({
"_id": cursor["_id"]
}, {
"$set": {
"mounts": cursor["newMounts"]
}
})
count += 1
print("\r", count, end="")
print("\n\nDone!!!")
I have JSON document recorded to MongoDB with structure like so:
[{ "SessionKey": "172e3b6b-509e-4ef3-950c-0c1dc5c83bab",
"Query": {"Date": "2020-03-04"},
"Flights": [
{"LegId":"13235",
"PricingOptions": [
{"Agents": [1963108],
"Price": 61763.64 },
{"Agents": [4035868],
"Price": 62395.83 }]},
{"LegId": "13236",
"PricingOptions": [{
"Agents": [2915951],
"Price": 37188.0}]}
...
The result I'm trying to get is "LegId":"sum_per_flight", in this case -> {'13235': (61763.64+62395.83), '13236': 37188.0} and then get flights with price < N
I've tried to run this pipeline for aggregation step (but it returns list of ALL prices - I don't know how to sum them up properly):
result = collection.aggregate([
{'$match': {'Query.Date': '2020-03-01'}},
{'$group': {'_id': {'Flight':'$Flights.LegId', 'Price':'$Flights.PricingOptions.Price'}}} ])
Also I've tried this pipeline, but it returns 0 for 'total_price_per_flight':
result = collection.aggregate({'$project': {
'Flights.LegId':1,
'total_price_per_flight': {'$sum': '$Flights.PricingOptions.Price'}
}})
You need to use $unwind to flatten Flights array to able iterate individually.
With $reduce operator, we iterate PricingOptions array and sum Price fields (accumulate prices).
The last step we return your documents into original structure. Before that, you may apply "get flights with price < N"
db.collection.aggregate([
{
"$match": {
"Query.Date": "2020-03-04"
}
},
{
$unwind: "$Flights"
},
{
$addFields: {
"Flights.LegId": {
$arrayToObject: [
[
{
k: "$Flights.LegId",
v: {
$reduce: {
input: "$Flights.PricingOptions",
initialValue: 0,
in: {
$add: [
"$$value",
"$$this.Price"
]
}
}
}
}
]
]
}
}
},
{
$group: {
_id: "$_id",
SessionKey: {
$first: "$SessionKey"
},
Query: {
$first: "$Query"
},
Flights: {
$push: "$Flights"
}
}
}
])
MongoPlayground
I want to iterate Mongodb database Arraylist items(TRANSACTION list) and remove Arraylist specific(TRANSACTION List) item using pymongo ?
I create Mongo collection as above using python pymongo. I want to iterate array list item using pymongo and remove final item only in Arraylist?
Data insert query using Python pymongo
# added new method create block chain_structure
def addCoinWiseTransaction(self, senz, coin, format_date):
self.collection = self.db.block_chain
coinValexists = self.collection.find({"_id": str(coin)}).count()
print('coin exists : ', coinValexists)
if (coinValexists > 0):
print('coin hash exists')
newTransaction = {"$push": {"TRANSACTION": {"SENDER": senz.attributes["#SENDER"],
"RECIVER": senz.attributes["#RECIVER"],
"T_NO_COIN": int(1),
"DATE": datetime.datetime.utcnow()
}}}
self.collection.update({"_id": str(coin)}, newTransaction)
else:
flag = senz.attributes["#f"];
print flag
if (flag == "ccb"):
print('new coin mined othir minner')
root = {"_id": str(coin)
, "S_ID": int(senz.attributes["#S_ID"]), "S_PARA": senz.attributes["#S_PARA"],
"FORMAT_DATE": format_date,
"NO_COIN": int(1),
"TRANSACTION": [{"MINER": senz.attributes["#M_S_ID"],
"RECIVER": senz.attributes["#RECIVER"],
"T_NO_COIN": int(1),
"DATE": datetime.datetime.utcnow()
}
]
}
self.collection.insert(root)
else:
print('new coin mined')
root = {"_id": str(coin)
, "S_ID": int(senz.attributes["#S_ID"]), "S_PARA": senz.attributes["#S_PARA"],
"FORMAT_DATE": format_date,
"NO_COIN": int(1),
"TRANSACTION": [{"MINER": "M_1",
"RECIVER": senz.sender,
"T_NO_COIN": int(1),
"DATE": datetime.datetime.utcnow()
}
]
}
self.collection.insert(root)
return 'DONE'
To remove the last entry, the general idea (as you have mentioned) is to iterate the array and grab the index of the last element as denoted by its DATE field, then update the collection by removing it using $pull. So the crucial piece of data you need for this to work is the DATE value and the document's _id.
One approach you could take is to first use the aggregation framework to get this data. With this, you can run a pipeline where the first step if filtering the documents in the collection by using the $match operator which uses standard MongoDB queries.
The next stage after filtering the documents is to flatten the TRANSACTION array i.e. denormalise the documents in the list so that you can filter the final item i.e. get the last document by the DATE field. This is made possible with the $unwind operator, which for each input document, outputs n documents where n is the number of array elements and can be zero for an empty array.
After deconstructing the array, in order to get the last document, use the $group operator where you can regroup the flattened documents and in the process use the group accumulator operators to obtain
the last TRANSACTION date by using the $max operator applied to its embedded DATE field.
So in essence, run the following pipeline and use the results to update the collection. For example, you can run the following pipeline:
mongo shell
db.block_chain.aggregate([
{ "$match": { "_id": coin_id } },
{ "$unwind": "$TRANSACTION" },
{
"$group": {
"_id": "$_id",
"last_transaction_date": { "$max": "$TRANSACTION.DATE" }
}
}
])
You can then get the document with the update data from this aggregate operation using the toArray() method or the aggregate cursor and update your collection:
var docs = db.block_chain.aggregate([
{ "$match": { "_id": coin_id } },
{ "$unwind": "$TRANSACTION" },
{
"$group": {
"_id": "$_id",
"LAST_TRANSACTION_DATE": { "$max": "$TRANSACTION.DATE" }
}
}
]).toArray()
db.block_chain.updateOne(
{ "_id": docs[0]._id },
{
"$pull": {
"TRANSACTION": {
"DATE": docs[0]["LAST_TRANSACTION_DATE"]
}
}
}
)
python
def remove_last_transaction(self, coin):
self.collection = self.db.block_chain
pipe = [
{ "$match": { "_id": str(coin) } },
{ "$unwind": "$TRANSACTION" },
{
"$group": {
"_id": "$_id",
"last_transaction_date": { "$max": "$TRANSACTION.DATE" }
}
}
]
# run aggregate pipeline
cursor = self.collection.aggregate(pipeline=pipe)
docs = list(cursor)
# run update
self.collection.update_one(
{ "_id": docs[0]["_id"] },
{
"$pull": {
"TRANSACTION": {
"DATE": docs[0]["LAST_TRANSACTION_DATE"]
}
}
}
)
Alternatively, you can run a single aggregate operation that will also update your collection using the $out pipeline which writes the results of the pipeline to the same collection:
If the collection specified by the $out operation already
exists, then upon completion of the aggregation, the $out stage atomically replaces the existing collection with the new results collection. The $out operation does not
change any indexes that existed on the previous collection. If the
aggregation fails, the $out operation makes no changes to
the pre-existing collection.
For example, you could run this pipeline:
mongo shell
db.block_chain.aggregate([
{ "$match": { "_id": coin_id } },
{ "$unwind": "$TRANSACTION" },
{ "$sort": { "TRANSACTION.DATE": 1 } }
{
"$group": {
"_id": "$_id",
"LAST_TRANSACTION": { "$last": "$TRANSACTION" },
"FORMAT_DATE": { "$first": "$FORMAT_DATE" },
"NO_COIN": { "$first": "$NO_COIN" },
"S_ID": { "$first": "$S_ID" },
"S_PARA": { "$first": "$S_PARA" },
"TRANSACTION": { "$push": "$TRANSACTION" }
}
},
{
"$project": {
"FORMAT_DATE": 1,
"NO_COIN": 1,
"S_ID": 1,
"S_PARA": 1,
"TRANSACTION": {
"$setDifference": ["$TRANSACTION", ["$LAST_TRANSACTION"]]
}
}
},
{ "$out": "block_chain" }
])
python
def remove_last_transaction(self, coin):
self.db.block_chain.aggregate([
{ "$match": { "_id": str(coin) } },
{ "$unwind": "$TRANSACTION" },
{ "$sort": { "TRANSACTION.DATE": 1 } },
{
"$group": {
"_id": "$_id",
"LAST_TRANSACTION": { "$last": "$TRANSACTION" },
"FORMAT_DATE": { "$first": "$FORMAT_DATE" },
"NO_COIN": { "$first": "$NO_COIN" },
"S_ID": { "$first": "$S_ID" },
"S_PARA": { "$first": "$S_PARA" },
"TRANSACTION": { "$push": "$TRANSACTION" }
}
},
{
"$project": {
"FORMAT_DATE": 1,
"NO_COIN": 1,
"S_ID": 1,
"S_PARA": 1,
"TRANSACTION": {
"$setDifference": ["$TRANSACTION", ["$LAST_TRANSACTION"]]
}
}
},
{ "$out": "block_chain" }
])
Whilst this approach can be more efficient than the first, it requires knowledge of the existing fields first so in some cases the solution cannot be practical.
This is my python code:
date1=datetime.datetime(2016,2,3)
cursor = collection.aggregate([
{"$match":{"EndTime":{"$gte":date1}}},
{"$project": { "EndTime":"$EndTime","StartTime":{ "$subtract": [ "$EndTime", "$TimeSpent"*1000]},"TimeSpent":"$TimeSpent"}},
{"$sort":{"StartTime":1}}
])
All my StartTime fields are None. How should I get the StartTime field as my python output.
Your pipeline should use the available arithmetic operators to do the computation; you are supposedly "multiplying" a string literal instead of using the $multiply operator hence why you are getting a null result, mongo
does not recognise this part "$TimeSpent"*1000 in { "$subtract": [ "$EndTime", "$TimeSpent"*1000] }.
Change your pipeline to use the $multiply operator within an expression instead and :
date1=datetime.datetime(2016,2,3)
cursor = collection.aggregate([
{ "$match": { "EndTime": { "$gte": date1 } } },
{
"$project": {
"EndTime": 1,
"TimeSpent": 1,
"StartTime": {
"$subtract": [
"$EndTime",
{ "$multiply": ["$TimeSpent", 1000] }
]
}
}
},
{ "$sort": { "StartTime": 1 } }
])