Collections
When deciding on data structures it is important to understand their tradeoffs. Choosing the wrong structure can create a bottleneck as the application scales, and migrating the state to the new data structures will come at a cost.
You can choose between two types of collections:
- Native collections (e.g.
Array,Map,Set), provided by the language - SDK collections (e.g.
IterableMap,Vector), provided by the NEAR SDK
Use native collections for small amounts of data that need to be accessed altogether, and SDK collections for large amounts of data that do not need to be accessed altogether.
If your collection has up to 100 entries, it's acceptable to use the native collection. For larger ones, prefer to use SDK collection. For comparison please refer to this benchmark.
Storage Management
Each time the contract is executed, the first thing it will do is to read the values and deserialize them into memory, and after the function finishes, it will serialize and write the values back to the database.
For native collections, the contract will fully load the collection into memory before any method executes. This happens even if the method you invoke does not use the collection. Know that this will have impact on GAS you spend for methods in your contract.
Storage Cost
Your contract needs to lock a portion of their balance proportional to the amount of data they stored in the blockchain. This means that:
- If more data is added the storage increases ↑, and your contract's balance decreases ↓.
- If data is deleted the storage decreases ↓, and your contract's balance increases ↑.
Currently, it costs approximately 1 Ⓝ to store 100kb of data.
Storage Constraints on NEAR
For storing data on-chain it’s important to keep in mind the following:
- There is a 4mb limit on how much you can upload at once
Let’s say for example, someone wants to put an NFT purely on-chain (rather than IPFS or some other decentralized storage solution) you’ll have almost an unlimited amount of storage but will have to pay 1 $NEAR per 100kb of storage used.
Users will be limited to 4MB per contract call upload due to MAX_GAS constraints. The maximum amount of gas one can attach to a given functionCall is 300TGas.
Your contract will panic if you try to store data but don't have NEAR to cover its storage cost
Be mindful of potential small deposit attacks
Native Collections
Native collections are those provided by the language, such as Array, Map, Set in Javascript, or Vec, HashMap, HashSet in Rust.
All entries in a native collection are serialized into a single value and stored together into the state. This means that every time a function execute, the SDK will read and deserialize all entries in the native collection.
Serialization & Storage Example
The array [1,2,3,4] will be serialized into the JSON string "[1,2,3,4]" in Javascript, and the Borsh byte-stream [0,0,0,4,1,2,3,4] in Rust before being stored
Native collections are useful if you are planning to store smalls amounts of data that need to be accessed all together
As the native collection grows, deserializing it from memory will cost more and more gas. If the collections grows too large, your contract might expend all the gas trying to read its state, making it fail on each function call
SDK Collections
The NEAR SDKs expose collections that are optimized for random access of large amounts of data. SDK collections are instantiated using a "prefix", which is used as an index to split the data into chunks. This way, SDK collections can defer reading and writing to the store until needed.
Serialization & Storage Example
The sdk array [1,2,3,4] with prefix "p" will be stored as the string "p" in the contract's attribute, and create four entries in the contract's storage: p-0:1, p-1:2...
SDK Collections' Features
| Type | Iterable | Clear All Values | Preserves Insertion Order | Range Selection |
|---|---|---|---|---|
Vector | ✅ | ✅ | ✅ | ✅ |
LookupSet | ||||
UnorderedSet | ✅ | ✅ | ✅ | |
IterableSet | ✅ | ✅ | ✅ | |
LookupMap | ||||
UnorderedMap | ✅ | ✅ | ✅ | |
IterableMap | ✅ | ✅ | ✅ | |
TreeMap | ✅ | ✅ | ✅ | ✅ |
SDK Collections' Time Complexities
| Type | Access | Insert | Delete | Search | Traverse | Clear |
|---|---|---|---|---|---|---|
Vector | O(1) | O(1)* | O(1)** | O(n) | O(n) | O(n) |
LookupSet | O(1) | O(1) | O(1) | O(1) | N/A | N/A |
UnorderedSet | O(1) | O(1) | O(1) | O(1) | O(n) | O(n) |
IterableSet | O(1) | O(1) | O(1) | O(1) | O(n) | O(n) |
LookupMap | O(1) | O(1) | O(1) | O(1) | N/A | N/A |
IterableMap | O(1) | O(1) | O(1) | O(1) | O(n) | O(n) |
TreeMap | O(1) | O(log n) | O(log n) | O(log n) | O(n) | O(n) |
* - to insert at the end of the vector using push_back (or push_front for deque)
** - to delete from the end of the vector using pop (or pop_front for deque), or delete using swap_remove which swaps the element with the last element of the vector and then removes it.
These collections are built to have an interface similar to native collections.
SDK collections are useful when you are planning to store large amounts of data that do not need to be accessed all together
Instantiation
All structures need to be initialized using a unique prefix, which will be used to index the collection's values in the account's state
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Notice how we use enums to ensure all collections have a different prefix. Another advantage of using enums is that they are serialized into a single byte prefix.
Loading...
Do not forget to use the schema to define how your contract's state is structured
from near_sdk_py import view, call, init
from near_sdk_py.collections import Vector, LookupMap, UnorderedMap, LookupSet, UnorderedSet
class MyContract:
@init
def new(self): # Create a Vector with prefix "v"
self.my_vector = Vector("v")
# Create a LookupMap with prefix "m"
self.my_lookup_map = LookupMap("m")
# Create an UnorderedMap with prefix "um"
self.my_unordered_map = UnorderedMap("um")
# Create a LookupSet with prefix "s"
self.my_lookup_set = LookupSet("s")
# Create an UnorderedSet with prefix "us"
self.my_unordered_set = UnorderedSet("us")
# For nested collections, use different prefixes
self.nested_maps = UnorderedMap("nested")
return True
@call
def create_nested_map(self, key: str):
# Create a new map that will be stored inside another map
inner_map = UnorderedMap(f"inner_{key}")
self.nested_maps[key] = inner_map
return {"success": True}
Be careful of not using the same prefix in two collections, otherwise, their storage space will collide, and you might overwrite information from one collection when writing in the other
Vector
Implements a vector/array which persists in the contract's storage. Please refer to the Rust and JS SDK's for a full reference on their interfaces.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import Vector
class VectorExample:
@init
def new(self):
# Create a Vector with prefix "v"
self.my_vector = Vector("v")
@call
def add_number(self, number):
# Append a value to the vector
self.my_vector.append(number)
return len(self.my_vector)
@view
def get_number(self, index):
# Get a value at specific index
try:
return self.my_vector[index]
except Exception:
return None
@view
def get_all_numbers(self):
# Convert entire vector to a list
return [num for num in self.my_vector]
LookupMap
Implements a map/dictionary which persists in the contract's storage. Please refer to the Rust and JS SDK's for a full reference on their interfaces.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import LookupMap
class LookupMapExample:
@init
def new(self):
# Create a LookupMap with prefix "m"
self.balances = LookupMap("m")
@call
def set_balance(self, account_id, amount):
# Set a value for a key
self.balances[account_id] = amount
return True
@view
def get_balance(self, account_id):
# Get a value for a key with a default
return self.balances.get(account_id, 0)
@call
def remove_balance(self, account_id):
# Remove a key
if account_id in self.balances:
del self.balances[account_id]
return True
return False
UnorderedMap / IterableMap
Implements a map/dictionary which persists in the contract's storage. Please refer to the Rust and JS SDK's for a full reference on their interfaces.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedMap
class UnorderedMapExample:
@init
def new(self):
# Create an UnorderedMap with prefix "um"
self.user_data = UnorderedMap("um")
@call
def set_user_data(self, account_id, data):
# Set a value for a key
self.user_data[account_id] = data
return True
@view
def get_user_data(self, account_id):
# Get a value for a key
try:
return self.user_data[account_id]
except Exception:
return None
@view
def list_all_users(self):
# Iterate through keys and values
return {
"keys": self.user_data.keys(),
"values": self.user_data.values(),
"items": self.user_data.items()
}
LookupSet
Implements a set which persists in the contract's storage. Please refer to the Rust and JS SDK's for a full reference on their interfaces.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import LookupSet
class LookupSetExample:
@init
def new(self):
# Create a LookupSet with prefix "s"
self.whitelist = LookupSet("s")
@call
def add_to_whitelist(self, account_id):
# Add a value to the set
self.whitelist.add(account_id)
return True
@view
def is_whitelisted(self, account_id):
# Check if a value exists in the set
return account_id in self.whitelist
@call
def remove_from_whitelist(self, account_id):
# Remove a value from the set
try:
self.whitelist.remove(account_id)
return True
except Exception:
return False
UnorderedSet / IterableSet
Implements a map/dictionary which persists in the contract's storage. Please refer to the Rust and JS SDK's for a full reference on their interfaces.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedSet
class UnorderedSetExample:
@init
def new(self):
# Create an UnorderedSet with prefix "us"
self.owners = UnorderedSet("us")
@call
def register_owner(self, account_id):
# Add a value to the set
self.owners.add(account_id)
return True
@view
def is_owner(self, account_id):
# Check if a value exists in the set
return account_id in self.owners
@view
def list_all_owners(self):
# Get all values as a list
return self.owners.values()
@call
def remove_owner(self, account_id):
# Try to remove a value if it exists
self.owners.discard(account_id)
return True
Tree
An ordered equivalent of Map. The underlying implementation is based on an AVL. You should use this structure when you need to: have a consistent order, or access the min/max keys.
- 🦀 Rust
- 🐍 Python
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import TreeMap
class TreeMapExample:
@init
def new(self):
# Create a TreeMap with prefix "tm"
self.scores = TreeMap("tm")
@call
def add_score(self, user_id, score):
# Set score for a user
self.scores[user_id] = score
return True
@view
def get_top_scores(self, limit=10):
# Get top scores using ordered keys
# This returns highest scores first
top_users = []
max_key = self.scores.max_key()
current_key = max_key
count = 0
while current_key is not None and count < limit:
top_users.append({
"user": current_key,
"score": self.scores[current_key]
})
current_key = self.scores.floor_key(current_key - 1) # Get next highest key
count += 1
return top_users
Nesting Collections
When nesting SDK collections, be careful to use different prefixes for all collections, including the nested ones.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
Loading...
Notice how we use enums that take a String argument to ensure all collections have a different prefix
Loading...
from near_sdk_py import view, call, init
from near_sdk_py.collections import UnorderedMap, Vector
from near_sdk_py.collections import create_prefix_guard
class NestedCollectionsExample:
@init
def new(self):
# Main map of users to their assets
self.user_assets = UnorderedMap("users")
@call
def add_asset(self, user_id, asset_id, metadata):
# Get or create the user's assets vector with a unique prefix
if user_id not in self.user_assets:
# Create a prefix guard to ensure unique prefixes for this user
prefix = f"assets:{user_id}"
# Create a new vector for this user's assets
self.user_assets[user_id] = Vector(prefix)
# Add the asset to the user's assets vector
user_assets = self.user_assets[user_id]
user_assets.append({
"asset_id": asset_id,
"metadata": metadata
})
# Update the vector in the map
self.user_assets[user_id] = user_assets
return True
@view
def get_user_assets(self, user_id):
if user_id not in self.user_assets:
return []
# Get all assets for the user
user_assets = self.user_assets[user_id]
return [asset for asset in user_assets]
In Python, we create unique prefixes for nested collections by including the parent's identifier in the prefix string. The SDK also provides a create_prefix_guard utility to help manage prefixes.
Error prone patterns
Because the values are not kept in memory and are lazily loaded from storage, it's important to make sure if a collection is replaced or removed, that the storage is cleared. In addition, it is important that if the collection is modified, the collection itself is updated in state because most collections will store some metadata.
Some error-prone patterns to avoid that cannot be restricted at the type level are:
- 🦀 Rust
use near_sdk::store::UnorderedMap;
let mut m = UnorderedMap::<u8, String>::new(b"m");
m.insert(1, "test".to_string());
assert_eq!(m.len(), 1);
assert_eq!(m.get(&1), Some(&"test".to_string()));
// Bug 1: Should not replace any collections without clearing state, this will reset any
// metadata, such as the number of elements, leading to bugs. If you replace the collection
// with something with a different prefix, it will be functional, but you will lose any
// previous data and the old values will not be removed from storage.
m = UnorderedMap::new(b"m");
assert!(m.is_empty());
assert_eq!(m.get(&1), Some(&"test".to_string()));
// Bug 2: Should not use the same prefix as another collection
// or there will be unexpected side effects.
let m2 = UnorderedMap::<u8, String>::new(b"m");
assert!(m2.is_empty());
assert_eq!(m2.get(&1), Some(&"test".to_string()));
// Bug 3: forgetting to save the collection in storage. When the collection is attached to
// the contract state (`self` in `#[near]`) this will be done automatically, but if
// interacting with storage manually or working with nested collections, this is relevant.
use near_sdk::store::Vector;
// Simulate roughly what happens during a function call that initializes state.
{
let v = Vector::<u8>::new(b"v");
near_sdk::env::state_write(&v);
}
// Simulate what happens during a function call that just modifies the collection
// but does not store the collection itself.
{
let mut v: Vector<u8> = near_sdk::env::state_read().unwrap();
v.push(1);
// The bug is here that the collection itself if not written back
}
let v: Vector<u8> = near_sdk::env::state_read().unwrap();
// This will report as if the collection is empty, even though the element exists
assert!(v.get(0).is_none());
assert!(
near_sdk::env::storage_read(&[b"v".as_slice(), &0u32.to_le_bytes()].concat()).is_some()
);
// Bug 4 (only relevant for `near_sdk::store`): These collections will cache writes as well
// as reads, and the writes are performed on [`Drop`](https://doc.rust-lang.org/std/ops/trait.Drop.html)
// so if the collection is kept in static memory or something like `std::mem::forget` is used,
// the changes will not be persisted.
use near_sdk::store::IterableSet;
let mut m: IterableSet<u8> = IterableSet::new(b"l");
m.insert(1);
assert!(m.contains(&1));
// This would be the fix, manually flushing the intermediate changes to storage.
// m.flush();
std::mem::forget(m);
m = IterableSet::new(b"l");
assert!(!m.contains(&1));
Pagination
Persistent collections such as IterableMap/UnorderedMap, IterableSet/UnorderedSet and Vector may
contain more elements than the amount of gas available to read them all.
In order to expose them all through view calls, we can use pagination.
- 🦀 Rust
- 🌐 JavaScript
- 🐍 Python
With Rust this can be done using iterators with Skip and Take. This will only load elements from storage within the range.
#[near(contract_state)]
#[derive(PanicOnDefault)]
pub struct Contract {
pub status_updates: IterableMap<AccountId, String>,
}
#[near]
impl Contract {
/// Retrieves multiple elements from the `IterableMap`.
/// - `from_index` is the index to start from.
/// - `limit` is the maximum number of elements to return.
pub fn get_updates(&self, from_index: usize, limit: usize) -> Vec<(AccountId, String)> {
self.status_updates
.iter()
.skip(from_index)
.take(limit)
.collect()
}
}
With JavaScript this can be done using iterators with toArray and slice.
/// Returns multiple elements from the `UnorderedMap`.
/// - `from_index` is the index to start from.
/// - `limit` is the maximum number of elements to return.
@view({})
get_updates({ from_index, limit }: { from_index: number, limit:number }) {
return this.status_updates.toArray().slice(from_index, limit);
}
# With Python this can be done using standard list slicing.
@view
def get_updates(self, from_index: int = 0, limit: int = 50) -> list:
"""Returns multiple elements from the collection with pagination.
Args:
from_index: The index to start from
limit: The maximum number of elements to return
Returns:
A list of elements from the collection
"""
# Get all values from the collection
all_items = self.status_updates.values()
# Apply pagination with list slicing
start = min(from_index, len(all_items))
end = min(start + limit, len(all_items))
return all_items[start:end]