Relational, save data in rows within tables.
MongoDB, save data in documents within collections.
basic things
db.collectionName.insert({"data":"Json like data"});
db.collectionName.find();
db.collectionName.find({"fieldName":"fieldValue"}); # case sensative
// multiple query can be made in same find
// common comparisons: $gt, $lt, $gte, $lte, $ne
// Array query operator,range query in array is like find("size":{"$elemMatch":{"$gt":8,"$lt":16}}), array act different than the document
// second params for find, to select the fields to show, {"fName1":true,"fName2":true} will set unselected ones to false.
// or {"fName1":false,"fName2":false} will set unchoosen one be true
// only have true & false when set _id to false
// find will return a cursor obj which contains 20 doc/block
cursor.sort({"field":order})
cursor.skip($x).limit($y)
db.collectionName.remove({"fieldName":"fieldValue"});
db.collectionName.update({"fieldName":"fieldValue"},{"$set":{"updateField":"updateValue"}}); // update a field of the first match, a third param {"multi": true} will update all
db.collectionName.update({"fieldName":"fieldValue"},{"$inc":{"updateField": incValue}}); //set third patam as {"upsert":true} to create a new field if not exist
// $unset to remove a field, $rename to rename a field
// use dot+index to update a ele in an array,
// or positional operator .$ to alert, but only for the first match per document
// $max to update if new value is > old, $min the reverse, $mul to multiply
// $pop to remove the 1st or last of an array, $push to add a value to the end of array
// $addToSet to add it if only it's not added
// $pull to remove from array
db.collectionName.update({"fName":"fValue"},{"uName":"uValue"}); // this is for overwriting
Embedded Documents and References, former will keep the data together, and modify together, while later can keep data rid of duplication, but should be taken great care on write.
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Is data using togehter ? if always together, Embed is best choice ,otherwise they’re not much different
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What’s the size of the data, small size will fit embed best, large size like thousands better choose Reference
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Will the data change often? if not, using Embed, if very often, reference
Aggregation (take stage operators)
db.collectionName.aggregate([{"$group":{"_id":"$groupField","accum":{"$stageOperator":"$field"}}}]);
Aggregation pipeline:
db.wands.aggregate([
{"$match":{"level_required":{"$lte":5}}},
{"$project":{"maker":true,"damage.magic":true,"_id":false}},
{"$group":{"_id":"$maker","max_damage":{"$max":"$damage.magic"}}},
{"$sort":{"max_damage":-1}},
{"$limit":4}
])