@memberjunction/core

The @memberjunction/core library is the foundational package of the MemberJunction ecosystem. It provides a comprehensive, tier-independent interface for metadata management, entity data access, view and query execution, transaction management, security, and more. All MemberJunction applications -- whether running on the server, in the browser, or via API -- depend on this package.

Installation

npm install @memberjunction/core
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Architecture Overview

flowchart TB
    subgraph Application["Application Layer"]
        style Application fill:#2d6a9f,stroke:#1a4971,color:#fff
        App["Your Application
(Angular, Node.js, etc.)"]
    end

    subgraph Core["@memberjunction/core"]
        style Core fill:#2d8659,stroke:#1a5c3a,color:#fff
        MD["Metadata"]
        BE["BaseEntity"]
        RV["RunView"]
        RQ["RunQuery"]
        RR["RunReport"]
        TG["TransactionGroup"]
        DS["Datasets"]
        LC["LocalCacheManager"]
        TM["TelemetryManager"]
        LOG["Logging"]
    end

    subgraph Providers["Provider Layer"]
        style Providers fill:#7c5295,stroke:#563a6b,color:#fff
        SP["Server Provider
(SQLServerDataProvider)"]
        CP["Client Provider
(GraphQLDataProvider)"]
    end

    subgraph Data["Data Layer"]
        style Data fill:#b8762f,stroke:#8a5722,color:#fff
        DB[("SQL Server
Database")]
        API["GraphQL API"]
    end

    App --> MD
    App --> BE
    App --> RV
    App --> RQ

    MD --> SP
    MD --> CP
    BE --> SP
    BE --> CP
    RV --> SP
    RV --> CP

    SP --> DB
    CP --> API
    API --> DB
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The package uses a provider model that allows the same application code to run transparently on different tiers. On the server, a SQLServerDataProvider communicates directly with the database. On the client, a GraphQLDataProvider routes requests through the GraphQL API. Your code does not need to know which provider is active.

Key Features

• Metadata-Driven Architecture -- Complete access to MemberJunction metadata including entities, fields, relationships, and permissions
• Entity Data Access -- Type-safe base classes for loading, saving, and manipulating entity records with dirty tracking and validation
• View Execution -- Powerful view running capabilities for both stored and dynamic views with filtering, pagination, and aggregation
• Query Execution -- Secure parameterized query execution with Nunjucks templates and SQL injection protection
• Transaction Management -- Support for grouped database transactions with atomic commits
• Provider Architecture -- Flexible provider model supporting different execution environments (server, client, API)
• Bulk Data Loading -- Dataset system for efficient loading of related entity collections
• Local Caching -- Intelligent local cache manager with TTL, LRU eviction, and differential updates
• Vector Embeddings -- Built-in support for AI-powered text embeddings and similarity search
• Enhanced Logging -- Structured logging with metadata, categories, severity levels, and verbose control
• Telemetry -- Session-level event tracking for performance monitoring and pattern detection
• BaseEngine Pattern -- Abstract engine base class for building singleton services with automatic data loading

Module Structure

flowchart LR
    subgraph index["index.ts (Public API)"]
        style index fill:#64748b,stroke:#475569,color:#fff
        EX["Exports"]
    end

    subgraph generic["generic/"]
        style generic fill:#2d6a9f,stroke:#1a4971,color:#fff
        metadata["metadata.ts"]
        baseEntity["baseEntity.ts"]
        providerBase["providerBase.ts"]
        entityInfo["entityInfo.ts"]
        securityInfo["securityInfo.ts"]
        interfaces["interfaces.ts"]
        transactionGroup["transactionGroup.ts"]
        baseEngine["baseEngine.ts"]
        compositeKey["compositeKey.ts"]
        logging["logging.ts"]
        runQuery["runQuery.ts"]
        runReport["runReport.ts"]
        localCacheManager["localCacheManager.ts"]
        telemetryManager["telemetryManager.ts"]
        util["util.ts"]
        queryCache["QueryCache.ts"]
        databaseProvider["databaseProviderBase.ts"]
    end

    subgraph views["views/"]
        style views fill:#2d8659,stroke:#1a5c3a,color:#fff
        runView["runView.ts"]
        viewInfo["viewInfo.ts"]
    end

    EX --> metadata
    EX --> baseEntity
    EX --> runView
    EX --> providerBase
    EX --> runQuery
    EX --> baseEngine
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Core Components

Metadata

The Metadata class is the primary entry point for accessing MemberJunction metadata and instantiating entity objects. It delegates to a provider set at application startup.

import { Metadata } from '@memberjunction/core';

const md = new Metadata();

// Refresh cached metadata
await md.Refresh();

// Access metadata collections
const entities = md.Entities;          // EntityInfo[]
const applications = md.Applications;  // ApplicationInfo[]
const currentUser = md.CurrentUser;    // UserInfo
const roles = md.Roles;               // RoleInfo[]
const queries = md.Queries;            // QueryInfo[]
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Metadata Properties

Helper Methods

// Look up entities by name or ID
const entityId = md.EntityIDFromName('Users');
const entityName = md.EntityNameFromID('12345');
const entityInfo = md.EntityByName('users');   // case-insensitive
const entity = md.EntityByID('12345');

// Record operations
const name = await md.GetEntityRecordName('Users', compositeKey);
const names = await md.GetEntityRecordNames(infoArray);
const isFavorite = await md.GetRecordFavoriteStatus(userId, 'Orders', key);
await md.SetRecordFavoriteStatus(userId, 'Orders', key, true);

// Dependencies and duplicates
const deps = await md.GetRecordDependencies('Orders', primaryKey);
const entityDeps = await md.GetEntityDependencies('Orders');
const dupes = await md.GetRecordDuplicates(duplicateRequest);

// Record merging
const mergeResult = await md.MergeRecords(mergeRequest);

// Record change history (built-in version control)
const changes = await md.GetRecordChanges<RecordChangeEntity>('Users', primaryKey);

// Transactions
const txGroup = await md.CreateTransactionGroup();
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GetEntityObject()

GetEntityObject<T>() is the correct way to create entity instances. It uses the MemberJunction class factory to ensure the proper subclass is instantiated and supports two overloads.

flowchart LR
    subgraph Creation["Entity Creation Flow"]
        style Creation fill:#2d6a9f,stroke:#1a4971,color:#fff
        GEO["GetEntityObject()"] --> CF["ClassFactory
Lookup"]
        CF --> SC["Subclass
Instantiation"]
        SC --> NR["NewRecord()
(auto-called)"]
        NR --> READY["Entity Ready"]
    end

    subgraph Loading["Entity Loading Flow"]
        style Loading fill:#2d8659,stroke:#1a5c3a,color:#fff
        GEO2["GetEntityObject()
with CompositeKey"] --> CF2["ClassFactory
Lookup"]
        CF2 --> SC2["Subclass
Instantiation"]
        SC2 --> LD["Load()
from Database"]
        LD --> READY2["Entity Ready
(with data)"]
    end
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Creating New Records

// NewRecord() is called automatically
const customer = await md.GetEntityObject<CustomerEntity>('Customers');
customer.Name = 'Acme Corp';
await customer.Save();

// Server-side with context user
const order = await md.GetEntityObject<OrderEntity>('Orders', contextUser);
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Loading Existing Records

import { CompositeKey } from '@memberjunction/core';

// Load by ID (most common)
const user = await md.GetEntityObject<UserEntity>('Users', CompositeKey.FromID(userId));

// Load by named field
const userByEmail = await md.GetEntityObject<UserEntity>('Users',
    CompositeKey.FromKeyValuePair('Email', 'user@example.com'));

// Load with composite primary key
const orderItem = await md.GetEntityObject<OrderItemEntity>('OrderItems',
    CompositeKey.FromKeyValuePairs([
        { FieldName: 'OrderID', Value: orderId },
        { FieldName: 'ProductID', Value: productId }
    ]));

// Server-side with context user
const order = await md.GetEntityObject<OrderEntity>('Orders',
    CompositeKey.FromID(orderId), contextUser);
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BaseEntity

The BaseEntity class is the foundation for all entity record manipulation. All entity classes generated by CodeGen extend it.

Field Access

// Type-safe property access (via generated getters/setters)
const name = user.FirstName;
user.FirstName = 'Jane';

// Dynamic field access
const value = user.Get('FirstName');
user.Set('FirstName', 'Jane');

// Field metadata
const field = user.Fields.find(f => f.Name === 'Email');
console.log(field.Dirty);        // Has the value changed?
console.log(field.IsUnique);     // Unique constraint?
console.log(field.IsPrimaryKey); // Primary key?
console.log(field.ReadOnly);     // Read-only field?
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Deprecated and Disabled Fields (Active-Status Enforcement)

Every entity field has a Status of Active (the default), Deprecated, or Disabled. The column stays physically present in the table and the EntityField instance is always created — status only governs whether code is allowed to use the field:

• Deprecated — still functional, but emits a batched console warning when accessed, nudging callers off it before removal.
• Disabled — throws on access; the field is off-limits even though the metadata and physical column remain.

Where enforcement happens (and where it deliberately does not). The status check lives at the field-access boundary that real code flows through — BaseEntity.Get(), BaseEntity.Set(), and BaseEntity.SetMany() — which is exactly what the generated strongly-typed accessors call:

// Generated accessor → BaseEntity.Get/Set → status enforced here
const s = agentRun.AgentState;      // Deprecated → warns; Disabled → throws
agentRun.Set('AgentState', value);  // same enforcement via the dynamic API
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It is not enforced on the low-level EntityField.Value accessor. Framework-internal machinery — dirty checking, validation, serialization (GetAll), record-change capture, and load-time hydration — reads EntityField.Value directly and is therefore exempt by construction. This is what keeps merely loading or saving a record that contains a deprecated column from false-warning on every operation: only genuine, code-initiated field access counts as "use."

SetMany() distinguishes the two via its ignoreActiveStatusAssertions parameter — the load/hydration paths pass true (populating from the database is not user use), while ordinary user-initiated SetMany() calls enforce status.

Fast path. Enforcement is gated on EntityInfo.HasInactiveFields, a value memoized once per entity definition. Entities whose fields are all Active (the overwhelming majority) pay only a single cached boolean check in Get/Set/SetMany — no per-field work and zero overhead in hot read/write loops.

Note: EntityField.ActiveStatusAssertions is retained as a deprecated no-op for backward compatibility. There is nothing to toggle at the field level anymore, since EntityField.Value no longer asserts.

Save and Delete

import { EntitySaveOptions } from '@memberjunction/core';

// Simple save
const success = await entity.Save();

// Save with options
const options = new EntitySaveOptions();
options.IgnoreDirtyState = true;     // Force save even if no changes detected
options.SkipEntityAIActions = true;  // Skip AI-related actions
options.SkipEntityActions = true;    // Skip entity actions
await entity.Save(options);

// Delete
await entity.Delete();
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GetAll() for Spread Operator

BaseEntity uses getter/setter properties, so the spread operator will not capture field values. Use GetAll() instead.

// WRONG -- spread ignores getter properties
const data = { ...entity };

// CORRECT -- GetAll() returns a plain object with all field values
const data = { ...entity.GetAll(), customField: 'value' };
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State Tracking and Events

BaseEntity provides comprehensive state tracking and lifecycle events.

import { BaseEntityEvent } from '@memberjunction/core';

// Check operation states
if (entity.IsSaving)   { /* Save in progress */ }
if (entity.IsDeleting) { /* Delete in progress */ }
if (entity.IsLoading)  { /* Load in progress */ }
if (entity.IsBusy)     { /* Any operation in progress */ }

// Subscribe to lifecycle events
const subscription = entity.RegisterEventHandler((event: BaseEntityEvent) => {
    switch (event.type) {
        case 'save_started':
            console.log(`Save started (${event.saveSubType})`); // 'create' or 'update'
            break;
        case 'save':
            console.log('Save completed');
            break;
        case 'delete_started':
            console.log('Delete started');
            break;
        case 'delete':
            console.log('Delete completed, old values:', event.payload?.OldValues);
            break;
        case 'load_started':
            console.log('Load started for key:', event.payload?.CompositeKey);
            break;
        case 'load_complete':
            console.log('Load completed');
            break;
        case 'new_record':
            console.log('NewRecord() called');
            break;
    }
});

// Unsubscribe when done
subscription.unsubscribe();
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Awaiting In-Progress Operations

// Wait for an in-progress save to complete before proceeding
await entity.EnsureSaveComplete();
await entity.EnsureDeleteComplete();
await entity.EnsureLoadComplete();
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Save Debouncing

Multiple rapid calls to Save() or Delete() are automatically debounced -- the second call receives the same result as the first.

const promise1 = entity.Save();
const promise2 = entity.Save(); // Returns same promise, no duplicate save
const [result1, result2] = await Promise.all([promise1, promise2]);
// result1 === result2
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Global Event Subscription

Monitor all entity operations across the application.

import { MJGlobal, MJEventType, BaseEntity, BaseEntityEvent } from '@memberjunction/core';

MJGlobal.Instance.GetEventListener(true).subscribe((event) => {
    if (event.event === MJEventType.ComponentEvent &&
        event.eventCode === BaseEntity.BaseEventCode) {
        const entityEvent = event.args as BaseEntityEvent;
        console.log(`[${entityEvent.baseEntity.EntityInfo.Name}] ${entityEvent.type}`);
    }
});
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Validation

const result = entity.Validate();
if (!result.Success) {
    for (const error of result.Errors) {
        console.error(`${error.Source}: ${error.Message}`);
    }
}
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CompositeKey

The CompositeKey class provides flexible primary key representation supporting both single and multi-field primary keys.

import { CompositeKey, KeyValuePair } from '@memberjunction/core';

// Single ID field
const key = CompositeKey.FromID('abc-123');

// Named single field
const key2 = CompositeKey.FromKeyValuePair('Email', 'user@example.com');

// Composite key
const key3 = CompositeKey.FromKeyValuePairs([
    { FieldName: 'OrderID', Value: orderId },
    { FieldName: 'ProductID', Value: productId }
]);

// Key operations
const value = key.GetValueByFieldName('ID');
const str = key.ToString();            // "ID=abc-123"
const concat = key.ToConcatenatedString(); // "abc-123"
const valid = key.Validate();           // { IsValid: boolean, ErrorMessage: string }
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RunView

The RunView class provides powerful view execution capabilities for both stored and dynamic queries.

flowchart LR
    subgraph Params["RunViewParams"]
        style Params fill:#2d6a9f,stroke:#1a4971,color:#fff
        SV["Stored View
(ViewID/ViewName)"]
        DV["Dynamic View
(EntityName + Filter)"]
    end

    subgraph RunView["RunView"]
        style RunView fill:#2d8659,stroke:#1a5c3a,color:#fff
        RV["RunView()"]
        RVS["RunViews()"]
    end

    subgraph Result["RunViewResult"]
        style Result fill:#b8762f,stroke:#8a5722,color:#fff
        S["Success"]
        R["Results[]"]
        TC["TotalRowCount"]
        AG["AggregateResults"]
    end

    SV --> RV
    DV --> RV
    DV --> RVS
    RV --> S
    RV --> R
    RVS --> S
    RV --> AG
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Basic Usage

import { RunView, RunViewParams } from '@memberjunction/core';

const rv = new RunView();

// Run a stored view by name
const result = await rv.RunView({
    ViewName: 'Active Users',
    ExtraFilter: "CreatedDate > '2024-01-01'"
});

// Run a dynamic view with entity objects returned
const typedResult = await rv.RunView<UserEntity>({
    EntityName: 'Users',
    ExtraFilter: 'IsActive = 1',
    OrderBy: 'LastName ASC, FirstName ASC',
    Fields: ['ID', 'FirstName', 'LastName', 'Email'],
    ResultType: 'entity_object'
});

// Access results
if (typedResult.Success) {
    const users = typedResult.Results; // UserEntity[]
    console.log(`Found ${users.length} users`);
}
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Batch Multiple Views

Use RunViews (plural) to execute multiple independent queries in a single operation.

const [users, roles, permissions] = await rv.RunViews([
    {
        EntityName: 'Users',
        ExtraFilter: 'IsActive = 1',
        ResultType: 'entity_object'
    },
    {
        EntityName: 'Roles',
        OrderBy: 'Name',
        ResultType: 'entity_object'
    },
    {
        EntityName: 'Entity Permissions',
        ResultType: 'simple'
    }
]);
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Aggregates

Request aggregate calculations that run in parallel with the main query, unaffected by pagination.

const result = await rv.RunView<OrderEntity>({
    EntityName: 'Orders',
    ExtraFilter: "Status = 'Completed'",
    MaxRows: 50,
    Aggregates: [
        { expression: 'SUM(TotalAmount)', alias: 'TotalRevenue' },
        { expression: 'COUNT(*)', alias: 'OrderCount' },
        { expression: 'AVG(TotalAmount)', alias: 'AverageOrder' }
    ]
});

// Aggregate results are in result.AggregateResults[]
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Keyset (Seek) Pagination — AfterKey

For background jobs and bulk processing that iterate through all records of a large entity, use AfterKey instead of StartRow. Keyset pagination stays O(log N) per page regardless of depth — StartRow/OFFSET pagination becomes progressively slower as the offset grows.

import { CompositeKey } from '@memberjunction/core';

let lastSeenKey: CompositeKey | undefined; // undefined => first page

while (true) {
    const result = await rv.RunView({
        EntityName: 'Tax Returns',
        ExtraFilter: 'AddressLine1 IS NOT NULL',
        AfterKey: lastSeenKey,
        MaxRows: 500,
        ResultType: 'entity_object'
    }, contextUser);

    if (!result.Success || result.Results.length === 0) break;
    for (const r of result.Results) { /* process */ }
    if (result.Results.length < 500) break; // partial page = end of data

    const last = result.Results[result.Results.length - 1];
    lastSeenKey = CompositeKey.FromID(last.ID);
}
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Constraints (throw AfterKeyNotSupportedError on violation):

• Entity must have a single-column primary key on a comparable type.
• OrderBy, if set, must reference only the PK column (any ASC/DESC direction).
• Cannot be combined with non-zero StartRow.

Keyset queries automatically bypass the server cache (read + write) — each call uses a different seek key, so caching them is pure overhead.

UI grid pagination (a few hundred pages of a few hundred rows) should stay on StartRow — keyset isn't necessary there. See KEYSET_PAGINATION_GUIDE.md for the full pattern, validation rules, and reference implementations.

// Defensive: catch the framework's typed error if you want to fall back to OFFSET
import { AfterKeyNotSupportedError } from '@memberjunction/core';

try {
    await rv.RunView({ EntityName: 'SomeEntity', AfterKey: key, MaxRows: 500 }, user);
} catch (e) {
    if (e instanceof AfterKeyNotSupportedError && e.Reason === 'CompositePK') {
        // entity has composite PK — fall back to StartRow-based iteration
    } else {
        throw e;
    }
}
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Helper: IsKeysetPaginationOrderableType(sqlTypeName) — returns true if a column type is acceptable as a keyset PK (essentially all standard SQL types; defensively rejects exotics like xml/sql_variant/varbinary).

ResultType and Fields Optimization

// entity_object -- full BaseEntity objects for mutation (Fields is ignored)
const mutableResult = await rv.RunView<UserEntity>({
    EntityName: 'Users',
    ResultType: 'entity_object'
});

// simple -- plain JavaScript objects for read-only use (use Fields for performance)
const readOnlyResult = await rv.RunView<{ ID: string; Name: string }>({
    EntityName: 'Users',
    Fields: ['ID', 'Name'],
    ResultType: 'simple'
});

// count_only -- returns only TotalRowCount, no rows
const countResult = await rv.RunView({
    EntityName: 'Users',
    ExtraFilter: 'IsActive = 1',
    ResultType: 'count_only'
});
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RunViewParams Reference

RunQuery

The RunQuery class provides secure execution of parameterized stored queries with Nunjucks templates and SQL injection protection.

import { RunQuery, RunQueryParams } from '@memberjunction/core';

const rq = new RunQuery();

// Execute by Query ID
const result = await rq.RunQuery({
    QueryID: '12345',
    Parameters: {
        StartDate: '2024-01-01',
        EndDate: '2024-12-31',
        Status: 'Active'
    }
});

// Execute by Query Name and Category Path
const namedResult = await rq.RunQuery({
    QueryName: 'Monthly Sales Report',
    CategoryPath: '/Sales/',
    Parameters: { Month: 12, Year: 2024 }
});

// Execute ad-hoc SQL (SELECT/WITH only — validated and run on read-only connection)
const adhocResult = await rq.RunQuery({
    SQL: 'SELECT TOP 100 Name, Status FROM __mj.vwUsers WHERE IsActive = 1'
});

if (result.Success) {
    console.log(`Rows: ${result.RowCount}, Time: ${result.ExecutionTime}ms`);
} else {
    console.error('Query failed:', result.ErrorMessage);
}
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SQL Security Filters

Parameterized queries use Nunjucks templates with built-in SQL injection protection filters:

RunReport

Execute reports by ID.

import { RunReport, RunReportParams } from '@memberjunction/core';

const rr = new RunReport();
const result = await rr.RunReport({ ReportID: '12345' });
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TransactionGroup

Group multiple entity operations into an atomic transaction.

import { Metadata } from '@memberjunction/core';

const md = new Metadata();
const txGroup = await md.CreateTransactionGroup();

// Add entities to the transaction
await txGroup.AddTransaction(entity1);
await txGroup.AddTransaction(entity2);

// Submit all operations as a single transaction
const results = await txGroup.Submit();
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Each TransactionResult in the returned array contains a Success flag. If any operation fails, all are rolled back.

Datasets

Datasets enable efficient bulk loading of related entity collections in a single operation, reducing database round trips.

flowchart TB
    subgraph Dataset["Dataset System"]
        style Dataset fill:#2d6a9f,stroke:#1a4971,color:#fff
        DEF["Dataset Definition
(name, description)"]
        ITEMS["Dataset Items
(entity, filter, code)"]
    end

    subgraph Loading["Loading Strategies"]
        style Loading fill:#2d8659,stroke:#1a5c3a,color:#fff
        FRESH["GetDatasetByName()
(always fresh)"]
        CACHED["GetAndCacheDatasetByName()
(uses cache if valid)"]
        CHECK["IsDatasetCacheUpToDate()
(check freshness)"]
        CLEAR["ClearDatasetCache()
(invalidate)"]
    end

    subgraph Storage["Cache Storage"]
        style Storage fill:#b8762f,stroke:#8a5722,color:#fff
        IDB["IndexedDB
(Browser)"]
        FS["File System
(Node.js)"]
        MEM["Memory
(Fallback)"]
    end

    DEF --> ITEMS
    ITEMS --> FRESH
    ITEMS --> CACHED
    CACHED --> IDB
    CACHED --> FS
    CACHED --> MEM
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import { DatasetItemFilterType } from '@memberjunction/core';

const md = new Metadata();

// Load dataset with caching
const dataset = await md.GetAndCacheDatasetByName('ProductCatalog');

// Load with item-specific filters
const filters: DatasetItemFilterType[] = [
    { ItemCode: 'Products', Filter: 'IsActive = 1' },
    { ItemCode: 'Categories', Filter: 'ParentID IS NULL' }
];
const filteredDataset = await md.GetAndCacheDatasetByName('ProductCatalog', filters);

if (filteredDataset.Success) {
    for (const item of filteredDataset.Results) {
        console.log(`Loaded ${item.Results.length} records for ${item.EntityName}`);
    }
}

// Check if cache is up-to-date
const isUpToDate = await md.IsDatasetCacheUpToDate('ProductCatalog');

// Clear cache
await md.ClearDatasetCache('ProductCatalog');
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BaseEngine

The BaseEngine abstract class is a singleton pattern for building engine/service classes that auto-load and auto-refresh data from entities or datasets.

import { BaseEngine, BaseEnginePropertyConfig } from '@memberjunction/core';

export class MyEngine extends BaseEngine<MyEngine> {
    public static get Instance(): MyEngine {
        return super.getInstance<MyEngine>();
    }

    private _myData: SomeEntity[] = [];

    public get MyData(): SomeEntity[] {
        return this.GetConfigData<SomeEntity>('_myData');
    }

    public async Config(forceRefresh?: boolean, contextUser?: UserInfo): Promise<void> {
        const params: Partial<BaseEnginePropertyConfig>[] = [
            {
                PropertyName: '_myData',
                EntityName: 'Some Entity',
                Filter: 'IsActive = 1',
                OrderBy: 'Name ASC',
                AutoRefresh: true      // Auto-refresh on entity save/delete events
            }
        ];
        return await this.Load(params, undefined, forceRefresh, contextUser);
    }
}

// Usage
await MyEngine.Instance.Config(false, contextUser);
const data = MyEngine.Instance.MyData;
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Key features:

• Singleton per class via BaseSingleton
• Declarative data loading via BaseEnginePropertyConfig
• Automatic refresh when entities are saved or deleted (debounced)
• Local caching support via CacheLocal and CacheLocalTTL options
• Supports both entity and dataset loading

Permission-Constrained Loading

When a user lacks read permissions on entities an engine loads, the engine enters a permission-constrained state instead of failing with errors or retrying endlessly. This is an all-or-nothing check — if any entity config is denied, all configs for that engine are skipped.

The GetConfigData<E>(propertyName) method is the canonical way for engine getters to expose loaded data. It checks the data map for permission denial and throws a PermissionConstrainedError if the config was skipped, preventing consumers from silently operating on empty arrays.

// Consumer that wants graceful degradation (optional feature)
if (!AIEngineBase.Instance.IsPermissionConstrained) {
    const models = AIEngineBase.Instance.Models;
    // ... render AI features
} else {
    // ... hide AI features, show notice
}

// Consumer that requires the data (hard error if missing)
const queries = QueryEngine.Instance.Queries; // throws PermissionConstrainedError if denied
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BaseEngineRegistry — cross-engine cache reverse lookup

Every BaseEngine registers itself with the process-wide BaseEngineRegistry on load, so the registry always knows which loaded engines cache which entities. You can use that to ask, from anywhere, "is this entity already fully in memory? if so, hand me the array — and don't go to the database."

This is the introspection behind the Admin → System Diagnostics "loaded engines" view, plus two reverse-lookup helpers:

import { BaseEngineRegistry, UserInfo } from '@memberjunction/core';

// All loaded engines that cache 'Users', unfiltered (full-set) caches first.
// Each match carries the engine, its config, and a LIVE pointer to the array.
const matches = BaseEngineRegistry.Instance.FindCachedEntity<UserInfo>('Users');
// matches[0] => { engineClassName, engine, config, records: UserInfo[], unfiltered }

// Or the one-liner: the best (unfiltered-preferred) cached array, or null.
const users = BaseEngineRegistry.Instance.TryGetCachedRecords<UserInfo>('Users', { unfilteredOnly: true });
if (users) {
    // Small/static entity already in memory — filter/sort locally, zero DB calls.
    const hits = users.filter(u => u.Name.toLowerCase().includes(q));
} else {
    // Not cached as a full set → fall back to a normal RunView against the DB.
}
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FindCachedEntity(entityName, { unfilteredOnly? }):

• Considers only loaded engines (a registered-but-unloaded engine has no data).
• Matches an engine config when Type === 'entity' and EntityName matches (case-insensitive, trimmed).
• Orders unfiltered caches first — a config with no Filter holds the complete entity set and is authoritative (safe for "show all" / in-memory search); filtered caches (a subset) come after. unfilteredOnly: true omits the filtered ones.
• Returns the engine's live array (not a copy) — read it, don't mutate it. When the config's ResultType is 'simple', rows are plain objects, not BaseEntity instances.
• Returns all matches when several engines cache the same entity, so the caller can pick (by engineClassName, by inspecting config, etc.).

TryGetCachedRecords(entityName, { unfilteredOnly? }) is the convenience wrapper — the best match's array, or null.

Why it's useful: UI and service code that needs to look up records for a small/static entity (FK pickers, dropdowns, validation) can serve the lookup from an already-loaded engine cache in a single line — no extra DB round-trip, no per-keystroke query — and transparently fall back to RunView when the entity isn't cached as a full set.

RegisterForStartup

The @RegisterForStartup decorator registers singleton engine classes (or any class implementing IStartupSink) with the StartupManager to automatically run configuration/setup during application boot.

import { RegisterForStartup, IStartupSink, IMetadataProvider, UserInfo } from '@memberjunction/core';

@RegisterForStartup({
    priority: 10,                 // Lower numbers run first
    severity: 'fatal',           // 'fatal' (aborts startup), 'error', 'warn', 'silent'
    description: 'My custom startup engine'
})
export class MyStartupEngine implements IStartupSink {
    public static get Instance(): MyStartupEngine {
        return super.getInstance<MyStartupEngine>();
    }

    public async HandleStartup(contextUser?: UserInfo, provider?: IMetadataProvider): Promise<void> {
        // Run configuration and initial load
        await this.Config(false, contextUser, provider);
    }
}
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Deferred Startup & Delay

For non-critical background services (like local AI model loading or vector pre-warming), you can set deferred: true to execute asynchronously without blocking the main application boot sequence.

You can also specify deferredDelay (in milliseconds) to wait a set duration after synchronous boot finishes before the startup manager triggers the task, preventing resource spikes during boot:

@RegisterForStartup({
    deferred: true,
    deferredDelay: 15000, // Delay background loading by 15 seconds
    description: 'Background AI Engine pre-warming'
})
export class AIEngine implements IStartupSink {
    // ...
}
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LocalCacheManager

The LocalCacheManager provides intelligent client-side caching for RunView and RunQuery results with TTL, LRU eviction, and differential updates.

import { LocalCacheManager } from '@memberjunction/core';

const cache = LocalCacheManager.Instance;

// Initialize with a storage provider
cache.Init(localStorageProvider);

// Cache statistics
const stats = cache.GetStats();
console.log(`Entries: ${stats.totalEntries}, Hits: ${stats.hits}, Misses: ${stats.misses}`);

// Clear all cached data
await cache.ClearAll();
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To use caching with RunView, set CacheLocal: true in your RunViewParams:

const result = await rv.RunView({
    EntityName: 'Products',
    ExtraFilter: 'IsActive = 1',
    CacheLocal: true,
    CacheLocalTTL: 300000  // 5 minutes
});
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To bypass all caching for a specific query (e.g., maintenance actions that need to see records inserted via direct SQL that bypassed BaseEntity.Save()), set BypassCache: true:

// Always hits the database — skips both cache reads and cache writes
const result = await rv.RunView({
    EntityName: 'Members',
    ExtraFilter: 'State IS NOT NULL',
    BypassCache: true,
    IgnoreMaxRows: true
});
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Cross-Server Cache Invalidation

When multiple MJAPI server instances share a Redis-backed ILocalStorageProvider, cache invalidation propagates automatically across all instances. The system uses two complementary mechanisms:

1. BaseEngine path (engine-managed data): When BaseEntity.Save() fires, BaseEngine catches the MJGlobal event, updates its in-memory arrays, and calls syncLocalCacheForConfig() → LocalCacheManager.UpsertSingleEntity() → Redis SetItem() → pub/sub notification. Other servers receive the notification via OnExternalCacheChange() and refresh their engine data.

2. LocalCacheManager path (all cached data): LocalCacheManager independently subscribes to MJGlobal BaseEntityEvent events. When any entity is saved or deleted, it finds all cached RunView fingerprints for that entity via a reverse index and either updates them in-place (unfiltered queries) or invalidates them (filtered queries). This ensures that all cached data — not just engine-managed data — stays consistent across servers.

MJAPI-A: BaseEntity.Save()
  → MJGlobal event
  → LocalCacheManager.HandleBaseEntityEvent()
  → Find all cached fingerprints for this entity
  → UpsertSingleEntity() or InvalidateRunViewResult()
  → Redis SetItem() → PUBLISH on mj:__pubsub__
  → MJAPI-B receives → DispatchCacheChange()
  → BaseEngine.OnExternalCacheChange() refreshes arrays
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Registering for change notifications:

// Engines and components can register callbacks for specific cache fingerprints
const fingerprint = LocalCacheManager.Instance.GenerateRunViewFingerprint(params);
const unsubscribe = LocalCacheManager.Instance.RegisterChangeCallback(
    fingerprint,
    (event: CacheChangedEvent) => {
        console.log(`Cache updated by server ${event.SourceServerId}`);
        // Refresh local data...
    }
);

// Cleanup when no longer needed
unsubscribe();
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Requirements for cross-server invalidation:

• Redis-backed ILocalStorageProvider (@memberjunction/redis-provider)
• enablePubSub: true in Redis provider config
• StartListening() called after provider creation
• OnCacheChanged wired to LocalCacheManager.DispatchCacheChange()

Storage Provider Implementations

LocalCacheManager and ProviderBase delegate persistence to an ILocalStorageProvider. MemberJunction ships with several implementations:

For production server deployments, the Redis provider is recommended. See the @memberjunction/redis-provider README for setup instructions.

Generic-typed interface

ILocalStorageProvider is generic — SetItem<T>(key, value, category?) and GetItem<T>(key, category?) thread the value's type through the call:

interface UserCacheEntry { userId: string; roles: string[]; }

await provider.SetItem<UserCacheEntry>('user:1', { userId: 'u-1', roles: ['admin'] }, 'Users');
const user = await provider.GetItem<UserCacheEntry>('user:1', 'Users');
//          ^^^^^ typed as UserCacheEntry | null — no .parse(), no casting
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Each implementation handles serialization for its medium internally:

• IndexedDB stores objects natively via the structured clone algorithm — Date, Map, Set, typed arrays, and nested objects are preserved as-is on retrieval. No JSON.parse on read — significantly faster for cache-heavy workloads.
• localStorage and Redis JSON-encode/decode internally because their underlying media are string-only. Date instances become ISO strings on round-trip; Map/Set become plain objects.
• In-memory stores object references directly — same identity returned on read.

Class instances (with prototype methods) lose their prototype on retrieval across all providers; store the underlying data shape (e.g. via entity.GetAll() for BaseEntity).

Batched reads via GetItems<T>

For workflows that need many cached entries at once — most notably the smart-cache-check warm-load path that reads ~85 fingerprints per coalesced engine batch — the interface exposes a batched read:

GetItems<T = unknown>(keys: string[], category?: string): Promise<Map<string, T | null>>;
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Returns a Map keyed by the input keys. Missing keys map to null. Implementations leverage their backend's native batching primitive:

• IndexedDB: single read transaction with N parallel get() calls inside it. Trades ~N transactions of overhead for one transaction's commit cost — significant on hot paths because IDB serializes transactions on the same object store. For 85 keys, this is the difference between ~425ms of IDB bookkeeping and ~10ms.
• Redis: one MGET command, one network round-trip, N values returned. ~N× faster than individual GET calls which each pay full RTT.
• localStorage / in-memory: implemented as a tight loop for API uniformity (no batching benefit on synchronous backends).

Used internally by LocalCacheManager.GetRunViewResults which the smart-cache-check flow calls in two passes (one for the per-fingerprint cache-status payload, one to materialize 'current' entries after the server response). Available to consumer code anywhere multiple cached entries are needed at once.

IndexedDB schema versioning

BrowserIndexedDBStorageProvider derives its IDB DB_VERSION from the @memberjunction/graphql-dataprovider package version (major * 1000 + minor). Patch releases share the same DB version (cache survives); minor releases trigger a one-time onupgradeneeded that wipes all object stores and recreates them empty. Cache repopulates on first use after the upgrade.

This is intentional: it sidesteps the "did this PR change cache format?" review burden — every minor naturally rolls forward to a clean cache. The cost is one slow page load per user per minor (~1s vs. the warm-load path), which is negligible for monthly LTS cadence and well below the perceptual threshold for "instant" on subsequent loads.

For emergency mid-minor cache schema changes, set MANUAL_CACHE_REVISION in storage-providers.ts to force an extra wipe within the same minor release.

Comprehensive Guide: For a deep dive into the full caching architecture — LocalCacheManager internals, differential updates, eviction policies, BaseEngine integration, Redis cross-server sync, GraphQL cache invalidation subscriptions, and deployment topologies — see the Caching & Pub/Sub Guide.

DatabaseProviderBase

An abstract class for server-side providers that need direct SQL execution and transaction control.

// Implemented by providers like SQLServerDataProvider
abstract class DatabaseProviderBase extends ProviderBase {
    abstract ExecuteSQL<T>(query: string, parameters?: unknown[], options?: ExecuteSQLOptions): Promise<T[]>;
    abstract BeginTransaction(): Promise<void>;
    abstract CommitTransaction(): Promise<void>;
    abstract RollbackTransaction(): Promise<void>;
}
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Provider Architecture

MemberJunction uses a provider model set once at application startup via SetProvider().

import { SetProvider } from '@memberjunction/core';

// The provider handles all data access transparently
SetProvider(myProvider);
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This single call configures the provider for Metadata, BaseEntity, RunView, RunReport, and RunQuery simultaneously.

Metadata Caching Optimization

Subsequent provider instances can reuse cached metadata from the first loaded instance to avoid redundant database calls in multi-user server environments.

const config = new ProviderConfigDataBase(
    connectionPool,
    '__mj',
    undefined,
    undefined,
    false  // ignoreExistingMetadata = false to reuse cached metadata
);
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Security and Permissions

const md = new Metadata();
const user = md.CurrentUser;
console.log(user.Email, user.IsActive, user.Type);

// Entity-level permissions
const entity = md.EntityByName('Orders');
console.log(entity.AllowCreateAPI);  // Can create via API?
console.log(entity.AllowUpdateAPI);  // Can update via API?
console.log(entity.AllowDeleteAPI);  // Can delete via API?

// Role-based permissions
const permissions = entity.Permissions; // EntityPermissionInfo[]
for (const perm of permissions) {
    console.log(perm.RoleName, perm.CanCreate, perm.CanRead, perm.CanUpdate, perm.CanDelete);
}
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Logging

Basic Logging

import { LogStatus, LogError } from '@memberjunction/core';

LogStatus('Operation completed successfully');
LogError('Something went wrong', null, additionalData);
LogStatus('Writing to file', '/logs/output.log');
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Enhanced Logging

import { LogStatusEx, LogErrorEx, IsVerboseLoggingEnabled, SetVerboseLogging } from '@memberjunction/core';

// Verbose-only logging
LogStatusEx({
    message: 'Detailed trace information',
    verboseOnly: true,
    category: 'BatchProcessor'
});

// Structured error logging
LogErrorEx({
    message: 'Failed to process request',
    error: new Error('Network timeout'),
    severity: 'critical',
    category: 'NetworkError',
    metadata: { url: 'https://api.example.com', timeout: 5000 },
    includeStack: true
});

// Control verbose logging
SetVerboseLogging(true);   // Browser: sets window.MJ_VERBOSE and localStorage
if (IsVerboseLoggingEnabled()) { /* ... */ }
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Verbose logging is controlled by the MJ_VERBOSE environment variable (Node.js), global variable, localStorage item, or URL parameter (browser).

TelemetryManager

Session-level performance tracking with pattern detection.

import { TelemetryManager } from '@memberjunction/core';

const tm = TelemetryManager.Instance;
tm.SetEnabled(true);

// Track an operation
const eventId = tm.StartEvent('RunView', 'MyComponent.LoadData', {
    EntityName: 'Users',
    ResultType: 'entity_object'
});
// ... perform operation
tm.EndEvent(eventId, { cacheHit: false, resultCount: 50 });

// Get patterns for analysis
const patterns = tm.GetPatterns({ category: 'RunView', minCount: 2 });
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Vector Embeddings Support

BaseEntity includes built-in methods for generating and managing vector embeddings for text fields.

import { BaseEntity, SimpleEmbeddingResult } from '@memberjunction/core';

// In a server-side entity subclass:
export class MyEntityServer extends MyEntity {
    public async Save(): Promise<boolean> {
        await this.GenerateEmbeddingsByFieldName([
            {
                fieldName: 'Description',
                vectorFieldName: 'DescriptionVector',
                modelFieldName: 'DescriptionVectorModelID'
            }
        ]);
        return await super.Save();
    }

    protected async EmbedTextLocal(textToEmbed: string): Promise<SimpleEmbeddingResult> {
        // Implement with your AI provider
        return { vector: [...], modelID: '...' };
    }
}
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Features:

• Dirty Detection -- Only generates embeddings when source text changes
• Null Handling -- Clears vector fields when source text is empty
• Parallel Processing -- Multiple embeddings generated concurrently

Ranked Entity Record Search (SearchEntity / SearchEntities)

A two-tier ranked-search API for finding the most relevant records of an entity for a free-text request. Distinct from the other lookups MJ already exposes — see the comparison below.

import { Metadata, EntitySearchResult } from '@memberjunction/core';

const md = new Metadata();

// Singular form — search one entity, return ranked record list
const results: EntitySearchResult[] = await md.SearchEntity({
    entityName: 'MJ: Entities',
    searchText: userRequestText,
    options: { mode: 'hybrid', topK: 10, weights: { lexical: 1.0, semantic: 1.5 }, contextUser }
});

// Plural form — search many entities in ONE round-trip
// Returns an array of arrays, aligned by input order
const groups = await md.SearchEntities([
    { entityName: 'Invoices',  searchText: 'overdue payments', options: { topK: 5, contextUser } },
    { entityName: 'Customers', searchText: 'overdue payments', options: { topK: 5, contextUser } },
    { entityName: 'Notes',     searchText: 'overdue payments', options: { topK: 5, contextUser } },
]);
// groups[0] = top Invoices, groups[1] = top Customers, groups[2] = top Notes
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Modes:

• lexical — substring / prefix matching on the entity's name field and any IncludeInUserSearchAPI fields.
• semantic — vector cosine against precomputed embeddings in MJ: Entity Record Documents.VectorJSON.
• hybrid (default) — weighted RRF blend of the two, tunable via options.weights and options.rrfK.

Configuration: semantic and hybrid modes require an Active EntityDocument of type Search registered for the target entity. The MJ install seeds one for MJ: Entities so the entity catalog is searchable out of the box; users enable it for other entities via metadata (see /metadata/entity-documents/).

Provider implementation: declared on IMetadataProvider, implemented polymorphically by each concrete provider. GenericDatabaseProvider runs the ranking in-process (embedding the query via AIEngine.EmbedTextLocal and querying SimpleVectorServiceProvider directly); GraphQLDataProvider proxies the whole batch to the server in one round-trip via the SearchEntities resolver. No registration or wiring required at startup.

How this differs from MJ's other search/lookup APIs

Picking the right one is straightforward: if you know the entity and want ranked records, use SearchEntity. If you know the candidate entities, use SearchEntities (plural). If you don't know which entity / want cross-source results, use SearchEngine.Search. For exact-name metadata lookup, use EntityByName.

Weighted Reciprocal Rank Fusion (ComputeRRF)

ComputeRRF is the canonical RRF implementation used wherever MJ blends ranked result lists (SearchEntity / SearchEntities hybrid mode, SearchEngine cross-scope fusion, dupe detection). It accepts an optional per-list weights array:

import { ComputeRRF, ScoredCandidate } from '@memberjunction/core';

const fused = ComputeRRF(
    [lexicalResults, semanticResults],
    /* k */ 60,
    /* weights */ [1.0, 1.5]   // semantic contributes 1.5× per rank position
);
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Formula: FusedScore(d) = Σ_i w_i / (k + rank_i(d)). Omitting weights is equivalent to all-ones — canonical unweighted RRF.

Utility Functions

import {
    TypeScriptTypeFromSQLType,
    FormatValue,
    CodeNameFromString,
    SQLFullType,
    SQLMaxLength
} from '@memberjunction/core';

// SQL type to TypeScript type mapping
TypeScriptTypeFromSQLType('nvarchar');   // 'string'
TypeScriptTypeFromSQLType('int');         // 'number'
TypeScriptTypeFromSQLType('bit');         // 'boolean'
TypeScriptTypeFromSQLType('datetime');    // 'Date'

// Format values for display
FormatValue('money', 1234.5);             // '$1,234.50'
FormatValue('nvarchar', longText, 2, 'USD', 50); // Truncated with '...'

// Generate code-safe names
CodeNameFromString('First Name');          // 'FirstName'
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Fire-and-Forget Entity Saves (BaseEntitySaveQueue)

BaseEntitySaveQueue is the entity-aware façade over @memberjunction/global's KeyedSerialTaskQueue for non-blocking persistence — writing observability/log rows (agent-run steps, action-execution logs, AI prompt runs, record-process details) without blocking the work that produced them on a DB round-trip.

import { BaseEntitySaveQueue } from '@memberjunction/core';

const queue = new BaseEntitySaveQueue();

// Fire-and-forget INSERT of a freshly NewRecord()'d entity.
queue.Insert(logEntity);

// Fire-and-forget UPDATE chained after that entity's INSERT. The mutation runs INSIDE the
// post-INSERT task, so the INSERT's finalizeSave reload can never revert it.
queue.Update(logEntity, (e) => { e.Set('EndedAt', new Date()); e.Set('Status', 'Completed'); });

// At a run/goal boundary, flush to await all pending saves + surface failure counts.
const { failures } = await queue.Flush();
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Why the Update(applyMutation) shape matters. A fire-and-forget INSERT serializes the entity's current fields and, on completion, BaseEntity.finalizeSave reloads the inserted row (init() + SetMany). Any field mutated on that same instance while the INSERT is in flight is reverted, and a force-persisted UPDATE then writes the stale values — the classic "stuck at Running" bug. Because the queue runs applyMutation inside the post-INSERT task, the mutation always lands after the reload, making that race impossible by construction.

Single-primary-key entities only; the queue logs (never throws) on a failed save, since these rows are observability and must not break the work that produced them.

Error Handling

RunView and RunQuery do NOT throw exceptions on failure. Always check Success:

const result = await rv.RunView<UserEntity>({
    EntityName: 'Users',
    ExtraFilter: 'IsActive = 1'
});

if (result.Success) {
    const users = result.Results;
} else {
    console.error('View failed:', result.ErrorMessage);
}
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For BaseEntity operations, check the return value and LatestResult:

const saved = await entity.Save();
if (!saved) {
    const error = entity.LatestResult;
    console.error('Save failed:', error.Message);

    if (error.ValidationErrors?.length > 0) {
        for (const ve of error.ValidationErrors) {
            console.error(`${ve.Source}: ${ve.Message}`);
        }
    }
}
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Best Practices

1. Always use Metadata.GetEntityObject() to create entity instances -- never use new directly
2. Use generic types with RunView<T> and GetEntityObject<T> for type safety
3. Use RunViews (plural) to batch multiple independent queries into one operation
4. Use ResultType: 'simple' with Fields for read-only data to improve performance
5. Check Success on RunView/RunQuery results -- these methods do not throw on failure
6. Pass contextUser in server-side code for proper security and audit tracking
7. Use GetAll() instead of the spread operator on BaseEntity instances
8. Override both Load() and LoadFromData() in subclasses that need custom loading logic
9. Use transactions for related operations that must succeed or fail together
10. Leverage entity metadata for dynamic UI generation and validation

Dependencies

Related Packages

Provider Implementations

Entity Extensions

UI Frameworks

AI Integration

Communication

Actions

Breaking Changes

v2.131.0

• Entity State Tracking: New IsSaving, IsDeleting, IsLoading, and IsBusy getters on BaseEntity.
• Operation Lifecycle Events: New event types save_started, delete_started, load_started, and load_complete.
• Delete Debouncing: Delete() now has the same debouncing behavior as Save().
• Global Event Broadcasting: All operation events are broadcast globally via MJGlobal.

v2.59.0

• Enhanced Logging Functions: New LogStatusEx and LogErrorEx with structured logging. Existing LogStatus and LogError remain fully backward compatible.
• Verbose Logging Control: New IsVerboseLoggingEnabled() and SetVerboseLogging() functions.

v2.58.0

• GetEntityObject() auto-calls NewRecord(): No longer necessary to call NewRecord() manually.
• UUID Generation: Entities with non-auto-increment uniqueidentifier primary keys get UUIDs automatically.

v2.52.0

• LoadFromData() is now async: Update calls to use await.

TypeScript Support

This library is written in TypeScript and provides full type definitions. All generated entity classes include proper typing for IntelliSense support. The package uses TypeScript strict mode and enforces strong typing throughout -- any types are not used.

License

ISC License - see LICENSE file for details.

Remote Operations (the 4th Data Primitive)

BaseRemotableOperation<TInput, TOutput> (defined in this package) is a typed, provider-routed server capability invoked from one call site on both the client (marshalled over GraphQL) and the server (in-process) — the missing peer of the three primitives MJCore already gives you:

graph LR
    subgraph "MJ data primitives — one call site, provider-routed"
        A["BaseEntity
record CRUD"]
        B["RunView
dynamic set reads"]
        C["RunQuery
stored queries"]
        D["BaseRemotableOperation
typed RPC"]
    end
    style D fill:#8b5cf6,color:#fff,stroke:#6d28d9
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entity.Save() · rv.RunView() · rq.RunQuery() · op.Execute() — same shape, same tier-agnostic DX.

Before this primitive, exposing one non-CRUD capability ("render a template", "run a process") to the browser meant hand-writing a stack — a TypeGraphQL resolver, a typed GraphQL client (or an inline gql string + a provider cast), an Angular wrapper, and the input/output types twice (client + server), kept in sync by hand. A Remote Operation replaces all of it with one typed object:

// typed in, typed out — identical on client and server; a wrong field is a compile error
const result = await new TemplateRunOperation().Execute({ templateID, data });
result.Output?.output;
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New operations are declared as MJ: Remote Operations metadata rows; CodeGen emits the typed base, and the body is written by hand (Manual), authored by an LLM from the row's Description and approved (AI), or left as emitted boilerplate (Default). Transport, auth, the long-running progress channel, and approval gating are written once in the framework and shared by every operation.

Visual before/after: See the Remote Operations Showcase — a diagram-driven tour of the layers this removes, built from two real migrations. (Best starting point for sharing with the team.)

Full Guide: See the Remote Operations Guide for when to use it (vs. an Action or a bespoke resolver), the three authoring modes, calling conventions, the auth chain, and long-running progress.

Virtual Entities

Virtual entities are read-only entities backed by SQL views rather than physical database tables. They appear in the metadata catalog alongside regular entities but have no underlying base table — only a base view. This makes them ideal for exposing aggregated data, cross-database views, or complex computed datasets as first-class entities.

flowchart LR
    subgraph Regular["Regular Entity"]
        RT[Base Table] --> RV[Base View]
        RV --> RE[Entity Metadata]
    end

    subgraph Virtual["Virtual Entity"]
        VV[SQL View Only] --> VE[Entity Metadata]
    end

    RE --> API[GraphQL API / RunView]
    VE --> API

    style Virtual fill:#e8d5f5,stroke:#7b2d8e
    style Regular fill:#d5e8f5,stroke:#2d5f8e
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Key Properties

Read-Only Enforcement

Virtual entities are enforced as read-only at multiple layers:

1. Runtime Guard — BaseEntity.CheckPermissions() blocks Create, Update, and Delete:

   if (this.EntityInfo.VirtualEntity &&
       (type === EntityPermissionType.Create ||
        type === EntityPermissionType.Update ||
        type === EntityPermissionType.Delete)) {
       throw new Error(
           `Cannot ${type} on virtual entity '${this.EntityInfo.Name}' — virtual entities are read-only`
       );
   }
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2. API Flags — AllowCreateAPI, AllowUpdateAPI, AllowDeleteAPI are all false
3. CodeGen — No stored procedures are generated

Using Virtual Entities

import { Metadata, RunView } from '@memberjunction/core';

// Read operations work identically to regular entities
const rv = new RunView();
const result = await rv.RunView({
    EntityName: 'Sales Summary',
    ExtraFilter: `RegionID = '${regionId}'`,
    ResultType: 'simple'
});

// Access metadata
const md = new Metadata();
const entity = md.EntityByName('Sales Summary');
console.log(entity.VirtualEntity);  // true
console.log(entity.BaseView);       // 'vwSalesSummary'

// Save() and Delete() will throw — virtual entities are read-only
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Full Guide: See Virtual Entities Guide for config-driven creation, LLM-assisted field decoration, field metadata, and troubleshooting.

IS-A Type Relationships (Type Inheritance)

MemberJunction supports IS-A type relationships (also called Table-Per-Type / TPT) where a child entity shares its parent's primary key and inherits all parent fields. This enables type hierarchies like Meeting IS-A Product or Webinar IS-A Meeting IS-A Product.

erDiagram
    Product ||--o{ Meeting : "IS-A"
    Product ||--o{ Publication : "IS-A"
    Meeting ||--o{ Webinar : "IS-A"

    Product {
        uuid ID PK
        string Name
        decimal Price
    }
    Meeting {
        uuid ID PK,FK
        datetime StartTime
        int MaxAttendees
    }
    Webinar {
        uuid ID PK,FK
        string PlatformURL
        boolean IsRecorded
    }
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How It Works

Child entities share the parent's primary key (same UUID). At runtime, BaseEntity uses persistent composition — each child instance holds a live reference to its parent entity through _parentEntity. All field access, dirty tracking, validation, and save/delete orchestration flow through this composition chain automatically.

EntityInfo IS-A Properties

const md = new Metadata();
const meeting = md.EntityByName('Meetings');

meeting.IsChildType;        // true — has a ParentID
meeting.ParentEntityInfo;   // EntityInfo for 'Products'
meeting.ParentChain;        // [ProductsEntityInfo] — all ancestors
meeting.AllParentFields;    // EntityFieldInfo[] — inherited fields (excludes PKs, timestamps)
meeting.ParentEntityFieldNames; // Set<string> — cached for O(1) lookup

const product = md.EntityByName('Products');
product.IsParentType;       // true — has child entities
product.ChildEntities;      // [MeetingsEntityInfo, PublicationsEntityInfo]
product.AllowMultipleSubtypes; // false — disjoint (default)
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BaseEntity Set/Get Routing

For IS-A child entities, parent fields are automatically routed to the parent entity:

const meetingEntity = await md.GetEntityObject<MeetingEntity>('Meetings');

// Own field — stored locally
meetingEntity.Set('StartTime', new Date());

// Parent field — automatically routed to ProductEntity._parentEntity
meetingEntity.Set('Name', 'Annual Conference');
meetingEntity.Get('Name'); // Returns from _parentEntity (authoritative)

// Dirty tracking spans the chain
meetingEntity.Dirty; // true if ANY field in chain is modified
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Disjoint vs Overlapping Subtypes

IS-A relationships support two modes, controlled by the parent entity's AllowMultipleSubtypes flag:

Disjoint (default) — A parent record can be at most ONE child type. The parent auto-chains to its single child via ISAChild, and save/delete delegates through the full chain.

// Product -> Meeting -> Webinar (disjoint chain)
const meeting = await md.GetEntityObject<MeetingEntity>('Meetings', key);
meeting.ISAChild;    // WebinarEntity (single child, auto-chained)
meeting.ISAChildren; // null (not overlapping)
meeting.LeafEntity;  // WebinarEntity (traverses to deepest child)
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Overlapping (AllowMultipleSubtypes = true) — A parent record can simultaneously exist as MULTIPLE child types. The parent does not auto-chain; instead, ISAChildren returns an informational list of which child entity types have records for this PK.

// Person -> [Members, Speakers, GoldMembers] (overlapping)
const person = await md.GetEntityObject<PersonEntity>('Persons', key);
person.ISAChild;     // null (no single child to chain to)
person.ISAChildren;  // [{entityName: 'Members'}, {entityName: 'Speakers'}, ...]
person.LeafEntity;   // PersonEntity itself (overlapping parent is its own leaf)

// Each child chains independently upward to Person
const member = await md.GetEntityObject<MemberEntity>('Members', key);
member.ISAParent;    // PersonEntity
member.Save();       // Saves Person -> Member (normal IS-A chain)
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Save & Delete Orchestration

• Save — Parent entities are saved first (inner-to-outer), then the child. On server, a shared SQL transaction wraps the entire chain.
• Delete (disjoint) — Child is deleted first, then parents. Disjoint subtype enforcement prevents a parent from being multiple child types simultaneously.
• Delete (overlapping) — Child is deleted, then the parent is checked for remaining children. If other children still exist, the parent is preserved. If no children remain, the parent is also deleted.

Record Change Propagation (Overlapping)

When saving through one branch of an overlapping hierarchy, Record Change entries are automatically propagated to sibling branches that share the same ancestor. This ensures complete audit history across all child types. Propagation is handled at the provider level (SQLServerDataProvider.PropagateRecordChangesToSiblings) using a single SQL batch for efficiency.

Full Guide: See IS-A Relationships Guide for the complete data model, runtime object model, save/delete orchestration sequences, overlapping subtypes, Record Change propagation, provider implementations, CodeGen integration, and troubleshooting.

Organic Keys (Cross-System Matching)

MemberJunction supports Organic Keys for establishing relationships between entities based on shared business data (email addresses, phone numbers, domains, etc.) rather than foreign key constraints. This is essential for cross-system integrations where external platforms (Mailchimp, QuickBooks, HubSpot, etc.) share data values but not primary keys.

Key capabilities:

• Direct matching: Field-to-field comparison with configurable normalization (LowerCaseTrim, Trim, ExactMatch, Custom)
• Compound keys: Match on multiple fields simultaneously (FirstName + LastName + DOB)
• Transitive matching: Bridge through intermediate tables via SQL views for multi-hop relationships
• Bidirectional: Configure on both sides for complete cross-system navigation
• CodeGen integration: Declare organic keys in additionalSchemaInfo.json — CodeGen creates bridge views, inserts metadata, and generates form panels automatically

// Access organic keys at runtime
const organicKeys = entity.OrganicKeys; // EntityOrganicKeyInfo[]

// Build query params for matching
const params = EntityInfo.BuildOrganicKeyViewParams(record, relatedEntity, organicKey);
// params.ExtraFilter = "LOWER(LTRIM(RTRIM([EmailAddress]))) = LOWER(LTRIM(RTRIM('john@acme.com')))"
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Full Guide: See Organic Keys Guide for the complete schema, all 4 query patterns, normalization strategies, CodeGen configuration, Angular UI integration, and an end-to-end setup walkthrough.

Entity Field Rules

EntityFieldRules is the metadata-aware layer on top of the pure field-rules engine in @memberjunction/global. The pure engine is deliberately metadata-blind — it computes a per-field diff from a plain Record<string, unknown> and an injected lookup resolver, so it runs anywhere. EntityFieldRules adds the things that only make sense when the target is a real MJ entity and that need this package's metadata layer:

Scope: the target is always an MJ entity; the source may be the entity's own fields plus an optional injected Context (a data context, a query result, an agent's output, related-entity lookups) — all data you already hold. When the other side is a live external system, that is the domain of @memberjunction/integration, which uses the same pure transform engine. EntityFieldRules is a writer to entities, not a bidirectional mapper.

import { EntityFieldRules } from '@memberjunction/core';
import type { FieldRuleSet } from '@memberjunction/global';

const ruleSet: FieldRuleSet = {
    Rules: [
        { TargetField: 'Description', Source: { Kind: 'formula', Expression: "fields.Name + ' (normalized)'" } },
        { TargetField: 'Status', Source: { Kind: 'static', Value: 'Inactive' }, Condition: 'DaysSinceActivity > 365' },
    ],
};

// 1) Pre-flight (synchronous, safe to run in a UX on every edit)
const check = EntityFieldRules.Validate('Accounts', ruleSet);
if (!check.Valid) console.warn(check.Errors);

// 2) Dry-run preview (computes the diff, writes nothing)
const rules = new EntityFieldRules(contextUser);
const preview = await rules.ApplyToEntity(account, ruleSet, { DryRun: true });
// preview.Changes → per-field old → new; preview.Saved === false

// 3) Apply for real (writes + Save → Record Changes versioning)
const result = await rules.ApplyToEntity(account, ruleSet);
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For bulk updates across a view / list / filtered set, the FieldRulesProcessor in @memberjunction/record-set-processor runs EntityFieldRules per record with batching, concurrency, and dry-run — that's the rules-based bulk-update tool.

Documentation

For detailed guides on specific topics, see the docs/ folder:

• Virtual Entities — Config-driven creation, LLM decoration, read-only enforcement
• IS-A Relationships — Type inheritance, save/delete orchestration, provider integration
• Organic Keys — Cross-system matching by shared business data (email, phone, domain), CodeGen integration, transitive views
• RunQuery Pagination — Parameterized queries with pagination support
• Full-Text Search — Database-native FTS via Metadata.FullTextSearch(), SQL Server FREETEXT / PostgreSQL tsvector, provider architecture, Knowledge Hub integration

Scoring Utilities

• ComputeRRF(rankedLists, k?) — Reciprocal Rank Fusion for combining ranked result lists from different retrieval methods. Score-scale independent — works on ordinal position, making it ideal for fusing vector similarity results with full-text search results. Located in @memberjunction/core (exported from src/generic/scoring/ReciprocalRankFusion.ts).
• ScoredCandidate — Interface for RRF input/output: { ID: string, Score: number, Metadata?: Record<string, unknown> }

Support

For support, documentation, and examples, visit MemberJunction.com.