So I have document like this
datatable: [{
data:[
["ABC", 123, 10, 1],
["ABC", 121, 10, 1],
["DDE", 13, 10, 1],
["OPP", 523, 10, 1]
]
}]
I want to select with a parameter "ABC" and would return arrays only with "ABC" like this:
datatable: [{
data:[
["ABC", 123, 10, 1],
["ABC", 121, 10, 1]
]
}]
Im starting with this code:
router.get("/", (req, res) => {
model.find({}).then(val=> {
res.send(val)
})
})
I cant find ways to find the value without the fieldname.
I tried using $elemMatch. Other ways needs a matching column name with the value.
Related
I have a DataFrame that has a website, categories, and keywords for that website.
Url | categories | keywords
Espn | [sport, nba, nfl] | [half, touchdown, referee, player, goal]
Tmz | [entertainment, sport] | [gossip, celebrity, player]
Goal [ [sport, premier_league, champions_league] | [football, goal, stadium, player, referee]
Which can be created using this code:
data = [{ 'Url': 'ESPN', 'categories': ['sport', 'nba', 'nfl'] ,
'keywords': ["half", "touchdown", "referee", "player", "goal"] },
{ 'Url': 'TMZ', 'categories': ["entertainment", "sport"] ,
'keywords': ["gossip", "celebrity", "player"] },
{ 'Url': 'Goal', 'categories': ["sport", "premier_league", "champions_league"] ,
'keywords': ["football", "goal", "stadium", "player", "referee"]},
]
df =pd.DataFrame(data)
For all the word in the keywords column, I want to get the frequency of categories associated with it. The results might look like this:
{half: {sport: 1, nba: 1, nfl: 1}, touchdown : {sport: 1, nba: 1,
nfl: 1}, referee: {sport: 2, nba: 1, nfl: 1, premier_league: 1,
champions_league:1 }, player: {sport: 3, nba: 1, nfl: 1,
premier_league: 1, champions_league:1 }, gossip: {sport:1,
entertainment:1}, celebrity: {sport:1, entertainment:1}, goal:
{sport:2, premier_league:1, champions_league:1, nba: 1, nfl: 1},
stadium:{sport:1, premier_league:1, champions_league:1} }
Since the columns contain lists, you can explode them to repeat a row once for each element per list:
result = (
df.explode("keywords")
.explode("categories")
.groupby(["keywords", "categories"])
.size()
)
Below is the Input_dict for data analysis:
input_dict =
{
"C:\\arm64\\lib_apple.so": { "func-abc": [5,6,7,8], "func-123":[1,1,1,1] },
"C:\\arm64\\lib_banana.so": { "func-123": [2,3,4], "func-rt": [0,0] },
"C:\\armeabi\\lib_banana.so": { "func-123": [1,0,0], "func-rt": [1,5] },
"C:\\armeabi\\lib2.so": { "func-0": [1]},
"C:\\x86\\lib_apple.so": { "func-so": [5,6,7,8], "func-123": [2,2,1,1] },
"C:\\x86\\lib_banana.so": { "func-rt": [2,0] },
"C:\\x86\\lib2.so": { "func-0": [1,2,3]}
}
The aim is to compare the 'values' of functions with same name of different architectures(arm64,armeabi,x86).
In other words, I want to compare the "lists" of functions(with same name) in different libraries(.so) files.
For example: Comparing func-123: [2,3,4] with func-123: [1,0,0] from arm64\lib_banana.so and armeabi\lib_banana.so respectively.
One of the desired output could be:
{ lib_apple.so: { func-123: [arm64,[1,1,1,1]],[x86,[2,2,1,1]]}}
You can restructure your function data to order by their name first, then supported architectures. Afterwards, print out those functions that appear in multiple architectures:
from collections import defaultdict
from pathlib import PureWindowsPath
lib2func = {
r'C:\arm64\lib_apple.so': { 'func-abc': [5,6,7,8], 'func-123': [1,1,1,1] },
r'C:\arm64\lib_banana.so': { 'func-123': [2,3,4], 'func-rt': [0,0] },
r'C:\armeabi\lib_banana.so': { 'func-123': [1,0,0], 'func-rt': [1,5] },
r'C:\armeabi\lib.so': {},
r'C:\armeabi\lib2.so': { 'func-0': [1]},
r'C:\x86\lib_apple.so': { 'func-so': [5,6,7,8], 'func-123': [2,2,1,1] },
r'C:\x86\lib_banana.so': { 'func-rt': [2,0] },
r'C:\x86\lib2.so': { 'func-0': [1,2,3] },
}
# restructure
func2arch = defaultdict(dict)
for lib_path, functions in lib2func.items():
path = PureWindowsPath(lib_path)
lib = path.name
arch = path.parent.name
for func_name, func_val in functions.items():
func2arch[(lib, func_name)][arch] = func_val
# find functions defined for multiple architectures
for (lib, func_name), arch_data in func2arch.items():
if len(arch_data) < 2:
continue # skip functions that only appear once
print(lib, func_name, arch_data)
gives
lib_apple.so func-123 {'arm64': [1, 1, 1, 1], 'x86': [2, 2, 1, 1]}
lib_banana.so func-123 {'arm64': [2, 3, 4], 'armeabi': [1, 0, 0]}
lib_banana.so func-rt {'arm64': [0, 0], 'armeabi': [1, 5], 'x86': [2, 0]}
lib2.so func-0 {'armeabi': [1], 'x86': [1, 2, 3]}
The above code assumes that library/function name pairs are unique.
I need to update (in bulk) many entities.
Each entity has a field that its value is an array.
I want to concat a whole array to the existed array in mongo.
For example:
Assume we have the field 'myField', and (its value) the array saved in mongo is: [4, 5, 6]
I want to concat the array [1, 2, 3] to this field, so the result:
myField: [1, 2, 3, 4, 5, 6]
I tried some options:
pushAll - but it is no longer available.
usePushEach: true, in options - not working, still get the same error:
"Unknown modifier: $pushAll. Expected a valid update modifier or pipeline-style update specified as an array"
I read about concat - but it is not looks compatiable.
Thanks in advance!
you can use $addToSet to add the values to existing array and avoid the duplicates like so,
[
{
id: 1,
values: [
1,
2,
3
]
}
]
db.collection.update({
id: 1
},
{
"$addToSet": {
values: {
"$each": [
5,
7,
1,
44
]
}
}
})
https://mongoplayground.net/p/S3HfWajg9r_
Having collection Measurement such as shown below:
{
"Data" : [ [-5, [[1, 1023.0], [2, 694.0]]], [-1, [[1, 0.0], [2, 20.0]]], [-3, [[1, 30.75], [2, 30.75]]] ]
}
it reflects c# structure of Dictionary<int, Dictionary<int, double>> - what I'd need to do is to write an update script which will add 5 to all the parental dictionary keys. How could this be done via mongo update script? So it would turn the object to look as follows:
{
"Data" : [ [0, [[1, 1023.0], [2, 694.0]]], [4, [[1, 0.0], [2, 20.0]]], [2, [[1, 30.75], [2, 30.75]]] ]
}
The only way to do this is programatically, i.e., looping over the Data array and updating each individually.
This is probably not the structure that you really want if you need to update things in this way. The problem lies with the ability to match elements in a nested array in that the current limitation is that you can only match the first position and reference that index only when doing an update.
We can't tell much about your purpose based on what you have presented, but what you probably need is something like this:
{
"Data" : [
{
"pos": 0,
"ref": -5,
"A": { "x": 1, "y": 1023.0 },
"B": { "x": 2, "y": 694.0 }
},
{
"pos": 1,
"ref": -1,
"A": { "x": 1, "y": 0.0},
"B": { "x": 2, "y": 20.0 }
},
{
"pos": 2,
"ref": -3,
"A": { "x": 1, "y": 30.75 },
"B": { "x": 2, "y": 30.75 }
}
]
}
Yet even that does not allow you to update in a single query. You can do it with one for each element though:
db.collection.update({"_id": id, "Data.pos": 0}, {"$inc":{"Data.$.ref": 5}});
db.collection.update({"_id": id, "Data.pos": 1}, {"$inc":{"Data.$.ref": 5}});
db.collection.update({"_id": id, "Data.pos": 3}, {"$inc":{"Data.$.ref": 5}});
And your current schema would not allow you to do even that. And at least all of the elements could be accessed in this way, which again they could not before.
In any case, updating all of the array elements at once is not possible other than in a loop:
db.collection.find({ "_id": id }).forEach(function(doc) {
doc.Data.forEach(function(data) {
data.ref += 5;
});
db.collection.update(
{ "_id": doc._id },
{ "$set": { "Data": doc.Data } }
);
})
Or some variant that might even do something like the first example rather that just replacing the whole array as this does. Your current structure would rely on looping through several nested arrays to do the same thing.
Of course if you regularly have to update all elements in this way, then consider something other than an array. Or live with how you have to update, according to what your data access needs are.
Read the documentation on how things can be handled and make you decisions from there.
user {
[
_id: xyz...,
Statuss["id1", "id2", "id3", "id4", "id5", "id6", "id7", "id8", "id9", "id10"]
]
}
I want to select Statuss skip(0).limit(5)
Tried:
collection.findOne({_id: id}, {Statuss: {$slice: [0, 5]}
but the result is:
Statuss["id1", "id2", "id3", "id4", "id5"]
want this result:
Statuss["id10", "id9", "id8", "id7", "id6"]
Tried this:
collection.findOne({_id: id}, {Statuss: {$slice: [5, 5]}