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In the context of relational databases, a domain is the set of all possible values that an attribute can take. **Formal Definition:** Let D be a domain (e.g., the set of all possible employee names, or the set of all valid salary values). A domain variable x is a variable such that for any valid assignment, x ∈ D—meaning x takes a value from domain D. **Key Insight:** While a tuple variable represents an entire row with multiple attributes, a domain variable represents just one atomic value—a single cell in the relational table. **Mathematical Foundation:** In set-theoretic terms, if we have a relation R with schema R(A₁, A₂, ..., Aₙ), each attribute Aᵢ is associated with a domain dom(Aᵢ). A domain variable xᵢ ranges over dom(Aᵢ), meaning: ``` xᵢ ∈ dom(Aᵢ) ``` This contrasts with a tuple variable t that would range over the entire relation: ``` t ∈ R, where t = (v₁, v₂, ..., vₙ) and each vᵢ ∈ dom(Aᵢ) ```72:T41f,Domain variables appear in three main contexts within DRC formulas: **1. Target List (Result Specification)** The target list specifies which domain values appear in the query result: ``` { | formula} ``` The variables x₁ through xₖ must all be free in the formula (not bound by quantifiers in the outermost scope) and must have their domains constrained by the formula. **2. Membership Predicates (Tuple Existence)** Membership predicates assert that certain domain values form a tuple in a relation: ``` Employee(e, n, s, d) -- Variables take values from a tuple in Employee Department(d, dn, m) -- Variables take values from a tuple in Department ``` **3. 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This seemingly subtle distinction leads to a fundamentally different query formulation style, one that would eventually inspire one of the most influential database query interfaces ever created: Query-by-Example (QBE).\n\nUnderstanding domain variables is essential because they represent a different level of abstraction—closer to the actual data values stored in the database. This perspective provides unique insights into query construction and has practical implications for how users interact with database systems."},"type":"text"},{"data":{"icon":"Target","title":"What You Will Learn","content":"By the end of this page, you will understand what domain variables are, how they differ fundamentally from tuple variables, how they range over attribute domains, and why this distinction matters for query formulation. You'll also see how domain variables provide a more granular view of data and enable alternative query expression styles.","variant":"info"},"type":"callout"}]},{"id":"what-are-domain-variables","title":"What Are Domain Variables?","content":[{"data":{"content":"$71"},"type":"text"},{"data":{"icon":"Lightbulb","title":"The Granularity Difference","content":"Think of it this way: A tuple variable is like selecting an entire row from a spreadsheet, while domain variables are like selecting individual cells. With tuple variables, you say 'give me this row.' With domain variables, you say 'give me the value in this column from a row where certain conditions hold.'","variant":"tip"},"type":"callout"},{"data":{"rows":[["What it represents","An entire tuple (row)","A single attribute value (cell)"],["Ranges over","Tuples in a relation","Values in a domain"],["Access notation","t.attribute (dot notation)","Variable names directly"],["Number needed per tuple","One per relation reference","One per attribute"],["Conceptual level","Row-level abstraction","Value-level abstraction"],["Closer analogy","Selecting a row","Selecting individual cells"]],"caption":"Tuple Variables vs Domain Variables","headers":["Aspect","Tuple Variables (TRC)","Domain Variables (DRC)"]},"type":"table"}],"titleType":"number","titleNumber":1},{"id":"understanding-domains","title":"Understanding Domains in Depth","content":[{"data":{"content":"Before we can fully appreciate domain variables, we must have a rigorous understanding of what domains are in the relational model.\n\n**Definition of Domain:**\n\nA domain is a named set of atomic (indivisible) values. Each domain has a logical definition that specifies what values belong to it. Domains can be:\n\n1. **Primitive domains** — Built-in types like INTEGER, REAL, CHAR(n), VARCHAR(n), DATE, BOOLEAN\n2. **User-defined domains** — Custom value sets defined for specific applications\n3. **Enumerated domains** — Finite sets of explicitly listed values\n\n**Examples of Domains:**"},"type":"text"},{"data":{"code":"-- Primitive domains (built-in types)\nEmployeeID_Domain = INTEGER (positive integers only)\nSalary_Domain = DECIMAL(10,2) (monetary values)\nName_Domain = VARCHAR(100) (character strings up to 100 chars)\n\n-- User-defined domains (SQL:1999 and later)\nCREATE DOMAIN PhoneNumber AS VARCHAR(20)\n CHECK (VALUE ~ '^[0-9-()+ ]+$');\n\nCREATE DOMAIN PositiveInteger AS INTEGER\n CHECK (VALUE > 0);\n\n-- Enumerated domains (finite value sets)\nDepartment_Domain = {'Engineering', 'Sales', 'HR', 'Finance', 'Marketing'}\nStatus_Domain = {'Active', 'Inactive', 'Pending', 'Terminated'}\nGrade_Domain = {'A', 'B', 'C', 'D', 'F'}","fileName":"domain_examples.sql","showLineNumbers":true},"type":"code"},{"data":{"content":"**Domain Compatibility:**\n\nIn the relational model, attributes are associated with domains, and meaningful comparisons can only be made between values from the same or compatible domains. For example:\n\n- Comparing `employee.salary` with `budget.amount` makes sense if both are numeric monetary values\n- Comparing `employee.name` with `department.id` doesn't make semantic sense even if both could be stored as strings\n\n**The Active Domain:**\n\nWhile a domain D defines all *possible* values, the **active domain** (also called the database domain) at any point in time is the set of values that actually appear in the current database instance. This distinction becomes important when we discuss safe queries later.\n\n```\nActive_Domain(A) = {t.A | t ∈ R} ⊆ dom(A)\n```\n\nThe active domain is always a subset of the full domain, containing only those values currently stored in the database."},"type":"text"},{"data":{"icon":"Info","title":"Why Domains Matter for DRC","content":"In DRC, when we declare a domain variable, we're implicitly stating which domain it ranges over. This gives the query evaluator precise information about what values the variable can take, which is crucial for query optimization and for ensuring query safety (finite results).","variant":"note"},"type":"callout"}],"titleType":"number","titleNumber":2},{"id":"declaration-and-binding","title":"Domain Variable Declaration and Binding","content":[{"data":{"content":"In Domain Relational Calculus, each domain variable must be **bound** to a specific domain before it can be used meaningfully in a query. This binding can be:\n\n1. **Explicit** — The domain is declared directly\n2. **Implicit** — The domain is inferred from usage in a membership condition\n\n**Explicit Declaration:**\n\nIn formal DRC notation, we might write:\n\n```\n{ | x ∈ dom(Name), y ∈ dom(Salary), z ∈ dom(DeptID), ...}\n```\n\nThis explicitly states that x ranges over names, y over salaries, and z over department IDs.\n\n**Implicit Binding Through Membership:**\n\nMore commonly, domain variables are bound implicitly through their use in **membership predicates**. When we write:\n\n```\n{ | Employee(x, y, z)}\n```\n\nThe variable x is implicitly bound to dom(Name) because it appears in the first position of the Employee relation, which has Name as its first attribute."},"type":"text"},{"data":{"items":["**Positional binding** — Variables are bound based on their position in a relation's attribute list. The first variable corresponds to the first attribute, second to second, and so on.","**Type consistency** — Once bound, a variable maintains its domain type throughout the query. You cannot compare a name-domain variable with a salary-domain value.","**Multiple occurrences** — A variable can appear multiple times in a formula, but all occurrences refer to the same value (like in algebra).","**Free vs. bound variables** — Variables in the target list are free (they define the output), while variables bound by quantifiers (∃, ∀) are bound within their scope."],"title":{"icon":"Target","text":"Key Binding Concepts","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**Binding Example in Detail:**\n\nConsider an Employee relation with schema:\n\n```\nEmployee(EmpID, Name, Salary, DeptID)\n```\n\nIf we write a DRC query:\n\n```\n{ | ∃e ∃d (Employee(e, n, s, d) ∧ s > 50000)}\n```\n\nHere:\n- `e` is bound to dom(EmpID) — the domain of employee IDs\n- `n` is bound to dom(Name) — the domain of employee names \n- `s` is bound to dom(Salary) — the domain of salary values\n- `d` is bound to dom(DeptID) — the domain of department IDs\n\nThe variables `n` and `s` are **free** (they appear in the target list), while `e` and `d` are **existentially bound** (they appear after ∃)."},"type":"text"},{"data":{"icon":"AlertCircle","title":"The Importance of Proper Binding","content":"Every domain variable must be bound either explicitly to a domain or implicitly through a relation membership condition. Unbound variables lead to undefined semantics and potentially infinite or meaningless results. Query safety ensures all variables are properly constrained.","variant":"warning"},"type":"callout"}],"titleType":"number","titleNumber":3},{"id":"relationship-tuples","title":"The Relationship Between Domain Variables and Tuples","content":[{"data":{"content":"Understanding how domain variables relate to tuples is crucial for mastering DRC. While we work with individual values, these values combine to form tuples.\n\n**The Tuple Reconstruction Principle:**\n\nIn DRC, a tuple is represented as an ordered list of domain variables. If a relation R has attributes A₁, A₂, ..., Aₙ, then a tuple in R is represented by domain variables x₁, x₂, ..., xₙ where:\n\n```\nR(x₁, x₂, ..., xₙ)\n```\n\nThis predicate is true if and only if the tuple (x₁, x₂, ..., xₙ) exists in relation R.\n\n**Visual Representation:**"},"type":"text"},{"data":{"rows":[["E001","Alice Chen","75000","D10"],["E002","Bob Smith","62000","D10"],["E003","Carol Davis","88000","D20"],["E004","David Lee","55000","D30"]],"caption":"Employee Relation Instance","headers":["EmpID (e)","Name (n)","Salary (s)","DeptID (d)"]},"type":"table"},{"data":{"content":"For the above relation:\n\n- `Employee('E001', 'Alice Chen', 75000, 'D10')` is **true**\n- `Employee('E001', 'Bob Smith', 75000, 'D10')` is **false** (no such tuple exists)\n- `Employee('E005', 'Eve Wilson', 90000, 'D40')` is **false** (no such tuple exists)\n\n**Contrast with TRC:**\n\nIn TRC, we would represent the same concept differently:\n\n```\nTRC: {t | Employee(t) ∧ t.Salary > 70000}\n One variable t represents the entire row\n Access attributes via t.Attribute notation\n\nDRC: { | ∃e ∃d (Employee(e, n, s, d) ∧ s > 70000)}\n Four variables e, n, s, d represent individual values\n No dot notation needed—variables ARE the values\n```\n\n**The Trade-off:**\n\nDRC requires more variable declarations (one per attribute potentially used), but eliminates the need for dot notation and makes the relationship between values and domains explicit. This verbosity becomes an advantage in certain contexts, particularly in visual query languages."},"type":"text"},{"data":{"icon":"Lightbulb","title":"When DRC Shines","content":"DRC is particularly intuitive when the query result requires only specific columns rather than entire tuples. Selecting Name and Salary from a 15-column table means working with just 2 domain variables in the target list, whereas TRC would still work with the full tuple and project at the end.","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":4},{"id":"domain-variables-formulas","title":"Domain Variables in Formulas","content":[{"data":{"content":"$72"},"type":"text"},{"data":{"code":"DRC Query Structure:\n═══════════════════\n\n{ | formula }\n\nComponents:\n───────────\n ::= | , \n \nformula ::= atomic_formula\n | ¬ formula\n | formula ∧ formula\n | formula ∨ formula\n | formula → formula\n | ∃ domain_var (formula)\n | ∀ domain_var (formula)\n\natomic_formula ::= R(var₁, var₂, ..., varₙ) -- Membership\n | var θ var -- Comparison (θ ∈ {=,≠,<,>,≤,≥})\n | var θ constant -- Constant comparison\n\nExample Query:\n─────────────\nFind names and salaries of employees earning over $50,000:\n\n{ | ∃e ∃d ( Employee(e, n, s, d) ∧ s > 50000 ) }\n\nBreakdown:\n• = Target list (result columns)\n• ∃e ∃d = Existential quantification (there exist values for e and d)\n• Employee(e, n, s, d) = Membership predicate (binding all four variables)\n• s > 50000 = Selection condition","fileName":"drc_formula_structure.txt","showLineNumbers":false},"type":"code"},{"data":{"content":"**Variable Scope and Quantification:**\n\nThe scope of a quantified variable extends to the smallest enclosing parentheses. Consider:\n\n```\n{ | ∃e ∃s ∃d (Employee(e, n, s, d) ∧ ∀m ∃dm ∃mm (Department(d, dm, m) → s > 60000))}\n```\n\nIn this (admittedly complex) example:\n\n- `n` is **free** — it appears in the target list\n- `e, s, d` are **existentially bound** in the outer scope\n- `m` is **universally bound** in the inner formula\n- `dm, mm` are **existentially bound** in the innermost scope\n\nThe scope rules ensure that each variable reference is unambiguous."},"type":"text"},{"data":{"icon":"Info","title":"The Freedom Principle","content":"A fundamental rule in DRC: Every variable in the target list must be free in the overall formula. You cannot return a value for a variable that's been existentially or universally bound—such a variable doesn't have a specific value to return.","variant":"note"},"type":"callout"}],"titleType":"number","titleNumber":5},{"id":"multiple-variables-joins","title":"Multiple Domain Variables and Joins","content":[{"data":{"content":"When queries involve multiple relations, domain variables from different membership predicates can be connected through **equality conditions**, effectively implementing joins.\n\n**Join Through Variable Reuse:**\n\nThe most elegant way to express a join in DRC is to use the **same variable** in corresponding positions of different relation predicates:\n\n```\nEmployee(e, n, s, d) ∧ Department(d, dn, m)\n```\n\nHere, the variable `d` appears in both predicates:\n- In Employee, it binds to DeptID (4th position)\n- In Department, it binds to the department key (1st position)\n\nBecause it's the same variable, the formula is only satisfied when both positions have the same value—this is the join condition!\n\n**Join Through Explicit Equality:**\n\nAlternatively, we can use different variables and add an explicit equality:\n\n```\nEmployee(e, n, s, d₁) ∧ Department(d₂, dn, m) ∧ d₁ = d₂\n```\n\nThis is semantically equivalent but more verbose."},"type":"text"},{"data":{"code":"Example: Find employee names with their department names\n\nSchema:\n Employee(EmpID, Name, Salary, DeptID)\n Department(DeptID, DeptName, ManagerID)\n\nMethod 1: Variable Reuse (Preferred)\n────────────────────────────────────\n{ | ∃e ∃s ∃d ∃m ( \n Employee(e, n, s, d) ∧ \n Department(d, dn, m) \n) }\n\nExplanation:\n• Variable 'd' binds to Employee.DeptID\n• Same 'd' binds to Department.DeptID\n• Natural join on department ID\n\nMethod 2: Explicit Equality\n───────────────────────────\n{ | ∃e ∃s ∃d₁ ∃d₂ ∃m ( \n Employee(e, n, s, d₁) ∧ \n Department(d₂, dn, m) ∧\n d₁ = d₂\n) }\n\nBoth queries produce identical results:\n┌─────────────┬─────────────┐\n│ Name │ DeptName │\n├─────────────┼─────────────┤\n│ Alice Chen │ Engineering │\n│ Bob Smith │ Engineering │\n│ Carol Davis │ Marketing │\n│ David Lee │ Sales │\n└─────────────┴─────────────┘","fileName":"drc_join_examples.txt","showLineNumbers":false},"type":"code"},{"data":{"content":"**Multi-Way Joins:**\n\nFor queries involving three or more relations, the same principles extend naturally:\n\n```\n{ | ∃e ∃s ∃d ∃m ∃p ∃ps \n Employee(e, n, s, d) ∧ \n Department(d, dn, m) ∧\n Project(p, pn, d) -- Project.DeptID = Employee.DeptID\n}\n```\n\nThis finds employees with their department names and project names for projects in their department.\n\n**Self-Joins with Domain Variables:**\n\nSelf-joins require careful variable management since we're referencing the same relation twice:\n\n```\n-- Find pairs of employees in the same department\n{ | ∃e₁ ∃s₁ ∃d ∃e₂ ∃s₂ (\n Employee(e₁, n₁, s₁, d) ∧ \n Employee(e₂, n₂, s₂, d) ∧\n e₁ < e₂ -- Avoid duplicate pairs and self-pairs\n)}\n```\n\nNote we use different variables `e₁, n₁, s₁` and `e₂, n₂, s₂` for the two references to Employee, but the same `d` to enforce the same-department condition."},"type":"text"},{"data":{"icon":"CheckCircle","title":"Elegant Join Semantics","content":"The variable-reuse join style in DRC is remarkably elegant: by simply using the same variable name in corresponding positions across relations, we express natural join semantics without explicit join operators or conditions. This declarative style says 'these must be the same value' implicitly.","variant":"success"},"type":"callout"}],"titleType":"number","titleNumber":6},{"id":"active-domain","title":"Domain Variables and the Active Domain","content":[{"data":{"content":"A critical concept when working with domain variables is the distinction between the **full domain** and the **active domain**.\n\n**The Full Domain Problem:**\n\nConsider a simple-looking query:\n\n```\n{ | ¬Employee(e, x, s, d)}\n```\n\n\"Find all names that are NOT employee names.\"\n\nIf x ranges over the full domain of names (all possible strings), the result is potentially infinite! This is the **safety problem** in DRC.\n\n**The Active Domain Solution:**\n\nThe **active domain** is the set of values that actually appear in the current database instance:\n\n```\nADOM = ⋃ { πAᵢ(R) | R is a relation, Aᵢ is an attribute of R }\n```\n\nFor safe query evaluation, we restrict domain variables to range over the active domain rather than the full theoretical domain."},"type":"text"},{"data":{"items":["**Finiteness** — The active domain is always finite (bounded by the total number of values in all relations).","**Dynamic** — The active domain changes as the database is updated. Inserting new values expands it; deleting the last occurrence of a value contracts it.","**Includes constants** — Constants appearing in the query are typically added to the active domain for evaluation purposes.","**Relation-specific** — We can speak of the active domain for a specific attribute or relation, not just globally.","**Safety criterion** — A query is safe if it can be evaluated using only active domain values and produces finite results."],"title":{"icon":"Target","text":"Active Domain Properties","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**Example: Active Domain Computation**\n\nGiven these relations:\n\n```\nEmployee(E001, 'Alice', 75000, D10)\nEmployee(E002, 'Bob', 62000, D10)\nDepartment(D10, 'Engineering', E001)\nDepartment(D20, 'Marketing', E003)\n```\n\nThe active domain for relevant attributes:\n- ADOM(Name) = {'Alice', 'Bob', 'Engineering', 'Marketing'}\n- ADOM(DeptID) = {D10, D20}\n- ADOM(EmpID) = {E001, E002, E003}\n- Global ADOM = Union of all attribute active domains\n\n**Safe Query Evaluation:**\n\nWhen evaluating a DRC query, we:\n1. Compute the active domain augmented with query constants\n2. Consider only assignments where domain variables take active domain values\n3. Evaluate the formula for all such assignments\n4. Return tuples where the formula evaluates to true\n\nThis ensures finite computation time and finite results."},"type":"text"},{"data":{"icon":"AlertCircle","title":"Safety Is Non-Negotiable","content":"The active domain restriction isn't just a performance optimization—it's a semantic necessity. Without it, many reasonable-looking queries would have undefined (infinite) results. We'll explore safety conditions in depth in a later page, but remember: domain variables must ultimately be constrained to produce meaningful results.","variant":"warning"},"type":"callout"}],"titleType":"number","titleNumber":7},{"id":"summary-path-forward","title":"Summary: Domain Variables","content":[{"data":{"content":"We've established the foundational understanding of domain variables—the building blocks of Domain Relational Calculus. Let's consolidate the key insights:"},"type":"text"},{"data":{"type":"ordered","items":["**Domain variables range over individual values** — Unlike tuple variables that represent entire rows, domain variables represent single atomic values from a specific domain.","**Domains define the space of possible values** — Each attribute has an associated domain that constrains what values are legal for that attribute.","**Variables are bound through membership predicates** — The expression R(x, y, z) binds x, y, z to the domains of R's attributes based on position.","**Joins use variable sharing** — Using the same variable in multiple relation predicates elegantly expresses join conditions without explicit operators.","**Free variables define results** — Variables in the target list must be free in the formula and determine what appears in the query output.","**Active domain ensures safety** — Restricting variable ranges to values actually in the database guarantees finite, meaningful results."],"title":{"icon":"CheckCircle","text":"Key Takeaways","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"**What's Next:**\n\nNow that we understand domain variables, we'll explore the complete **DRC syntax**—the formal grammar that governs how DRC queries are constructed. We'll learn the precise rules for forming valid queries, the operators available, and how complex conditions are expressed using logical connectives and quantifiers."},"type":"text"},{"data":{"icon":"CheckCircle","title":"Page Complete","content":"You now understand domain variables—the fundamental building blocks of Domain Relational Calculus. You know how they differ from tuple variables, how they bind to domains, how they participate in formulas, and why the active domain constraint is essential. Next, we'll use this foundation to learn the complete DRC syntax.","variant":"success"},"type":"callout"}],"titleType":"number","titleNumber":8}],"isLocked":false},{"id":"seed_ac620c7620467102ae777278441c0c37","title":"DRC Syntax: The Formal Grammar","order":1,"content":null,"isLocked":true},{"id":"seed_fa73b3dd33f4f14f983cb7c8c2f06829","title":"Comparison with TRC: Two Perspectives on Declarative Queries","order":2,"content":null,"isLocked":true},{"id":"seed_7352d2ca5df0a6e0e268eb9164d577ef","title":"Query Examples: DRC in Practice","order":3,"content":null,"isLocked":true},{"id":"seed_4ed4d8c3e8ed8b5d7ab43c469e7a7d8b","title":"QBE Connection: From Theory to Visual Interface","order":4,"content":null,"isLocked":true}]}},"dataUpdateCount":1,"dataUpdatedAt":1792284856586,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["learningContent","getModule"],{"input":{"slug":"domain-relational-calculus"},"type":"query"}],"queryHash":"[[\"learningContent\",\"getModule\"],{\"input\":{\"slug\":\"domain-relational-calculus\"},\"type\":\"query\"}]"},{"dehydratedAt":1792284856647,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792284856587,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["learningContent","getProgress"],{"input":{"moduleId":"seed_8fe457cc5aa3682c9c16122752ff2f64"},"type":"query"}],"queryHash":"[[\"learningContent\",\"getProgress\"],{\"input\":{\"moduleId\":\"seed_8fe457cc5aa3682c9c16122752ff2f64\"},\"type\":\"query\"}]"},{"dehydratedAt":1792284856647,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792284856587,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["feedback","get"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_ac620c7620467102ae777278441c0c37"},"type":"query"}],"queryHash":"[[\"feedback\",\"get\"],{\"input\":{\"contentId\":\"seed_ac620c7620467102ae777278441c0c37\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792284856647,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792284856587,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["feedback","getUserLike"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_ac620c7620467102ae777278441c0c37"},"type":"query"}],"queryHash":"[[\"feedback\",\"getUserLike\"],{\"input\":{\"contentId\":\"seed_ac620c7620467102ae777278441c0c37\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792284856647,"state":{"data":{"json":[]},"dataUpdateCount":1,"dataUpdatedAt":1792284856587,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["highlights","getHighlights"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_ac620c7620467102ae777278441c0c37"},"type":"query"}],"queryHash":"[[\"highlights\",\"getHighlights\"],{\"input\":{\"contentId\":\"seed_ac620c7620467102ae777278441c0c37\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792284856647,"state":{"data":"$undefined","dataUpdateCount":0,"dataUpdatedAt":0,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"pending","fetchStatus":"fetching"},"queryKey":[["highlights","getPopularHighlights"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_ac620c7620467102ae777278441c0c37","minCount":2},"type":"query"}],"queryHash":"[[\"highlights\",\"getPopularHighlights\"],{\"input\":{\"contentId\":\"seed_ac620c7620467102ae777278441c0c37\",\"contentType\":\"LEARNING_PAGE\",\"minCount\":2},\"type\":\"query\"}]","promise":"$@73"}]},"children":"$L74"}]