Major Objects
Use Major Objects for fast in-memory handling of large amount of data that is thread-safe but must be persisted. Support complex objects with simple keys, fast lookup by multiple keys, serialization to multiple persistent layers, and fast DRY schema changes.
Major Objects
- Use an unordered_set of const pointers to objects derived from PersistentIDObject (see below)
- The main container's primary key is always db_id
- Always use the db_id for foreign keys
- Other containers can be created using other members as keys; the only cost is for a new set of pointers (not objects!)
- For other unordered_sets, just define new hash functions
- Other useful containers are sorted_vector and map (<key,value> pair)
PersistentIDObject
- Add a dirty flag to all objects, set to true on any change that must be persisted
- Use an internal in-memory counter to generate the next db_id for a newly created object
- This means that when creating new objects, there is NO NEED to access db, VERY IMPORTANT!
- Use delayed-write tactics to write all dirty objects on idle time
Memory Model
- Use a Datastore manager (aka "MemoryModel") to hold sets
- It can look up objects by any key, and strip away const to return a mutable object. NOTE that the user must not damage the key values!
- Derive a class from the memory model for persistence; it can use any persistence method (local, remote, sql, nosql, etc.).
- Make sure that the base MemoryModel class is concrete not abstract, thread-safe and self-contained; this makes parallel calculations trivial, helps scalability, etc.
Schema Driven
- Schema is shared across memory objects and every persistence layer. Follow a DRY pattern by generating all code from a common schema definition.
- JSON schema is elegant as it is as simple as possible but no less, always use it. Essential tools:
- quicktype - use npm to install it and to incorporate code generation into CI
- JSON formatter
- Always provide a constructor with a single db_id parameter, defaulted to UNSAVED; this serves two purposes:
- no-param constructor for reflection via quicktype
- id constructor for use as key for unsorted_set::find()
THE RESULT
- Fast efficient unsorted_set<PersistentIDObject*> containers that can be automatically serialized to/from any database layer
- Fast supplemental in-memory indexes into objects wherever needed
- DRY code that allows schema changes within a rapid, complete, and simplified codebase
Delayed delete pattern
1) to dynamically delete an object: a) ba.setDeleted(); b) do not remove from any container indexes c) but fix the index sorting, flags, etc, as if the object were gone, so the program will function as if it is! eg: do not remove from runsByRank_, but adjust all other ranking as if the run was gone 2) include deleted status in active check, etc.: // NOTE use the direct function rather than !bFunc(), as deleted objects return false for both. bool bActive() const { return b_active_ && !bDeleted(); } bool bInactive() const { return !b_active_ && !bDeleted(); } --- for (auto& psr: runsByRank_) { if (psr->bDeleted()) continue; ... 3) all deletion work is done in MemoryModel::saveDirtyObjectsAsNeeded(), see that code a) deletion check should happen in delayed write check: if (pau->bDirtyOrDeleted()) bNeeded = true; b) if bNeeded, always do deletions first, starting with greatest grandparent container, to minimize work c) use the erase-remove pattern to remove all deleted items in one loop see code here for reference implementation: BrokerAccount::removeDeletedStockRuns() i) iterate and remove item from all secondary indices ii) iterate primary index, and use the lambda of the erase-remove operation to delete memory allocation and remove db record iii) associative container iterators can be safely deleted directly sequential containers like vector require use of erase-remove idiom see reference implementation for example code!