Janady13/missionmatch / db/queries/candidates.sql

Source identity

Field	Recorded value
Source type	GitHub source
Original record	Janady13/missionmatch / db/queries/candidates.sql
Date	Not specified in source
Repository	Janady13/missionmatch
Revision	39df94f92b2a33f852481fe1954dabed841524bb
Branch	w0-aedt-compliance
Path or archive member	db/queries/candidates.sql
Original SHA-256	fd22839d7add84aaeb289bf1c89534b21431c0107c7e5ca966b375f004d12b6c
Git blob SHA	874e6d069a319e400a05c55c22c0d99316149d6e
Reading-copy SHA-256	fd22839d7add84aaeb289bf1c89534b21431c0107c7e5ca966b375f004d12b6c

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-- name: CreateCandidate :one
INSERT INTO candidates (
    organization_id, full_name, email, headline,
    clearance_level, clearance_poly, clearance_status,
    years_experience, location, remote, relocatable, available, resume_embedding
) VALUES ($1,$2,$3,$4,$5,$6,$7,$8,$9,$10,$11,$12,$13)
RETURNING *;

-- name: GetCandidate :one
SELECT * FROM candidates WHERE id = $1 AND deleted_at IS NULL;

-- name: ListCandidates :many
SELECT * FROM candidates
WHERE deleted_at IS NULL
ORDER BY created_at DESC
LIMIT $1 OFFSET $2;

-- name: ListCandidatesForIntel :many
-- Available (staffable) candidates first, most recently updated next, so the workforce intelligence
-- surface leads with the talent you can deploy and newly staffed or sourced people are always scored.
SELECT * FROM candidates
WHERE deleted_at IS NULL
ORDER BY available DESC, updated_at DESC, created_at DESC
LIMIT $1;

-- name: SoftDeleteCandidate :exec
UPDATE candidates SET deleted_at = now(), updated_at = now() WHERE id = $1;

-- name: AnonymizeCandidate :execrows
-- Right to erasure as anonymize in place: wipe the identifying PII while KEEPING the row so the de
-- identified scored outcomes (slate_members) and the demographic bucket survive for the adverse impact
-- record. Once the name, email, contact, and resume vector are gone the row is no longer personal data,
-- so erasure is satisfied and the compliance history is preserved. Idempotent on anonymized_at.
UPDATE candidates SET
    full_name        = '[erased]',
    email            = NULL,
    headline         = NULL,
    location         = NULL,
    resume_embedding = NULL,
    external_id      = NULL,
    available        = false,
    anonymized_at    = now(),
    updated_at       = now()
WHERE id = $1 AND anonymized_at IS NULL;

-- name: AddCandidateSkill :exec
INSERT INTO candidate_skills (organization_id, candidate_id, skill_id)
VALUES ($1,$2,$3)
ON CONFLICT (candidate_id, skill_id) DO NOTHING;

-- name: ListCandidateSkills :many
SELECT s.id, s.name
FROM candidate_skills cs
JOIN skills s ON s.id = cs.skill_id
WHERE cs.candidate_id = $1
ORDER BY s.name;

-- name: AddCandidateCertification :exec
INSERT INTO candidate_certifications (organization_id, candidate_id, name)
VALUES ($1,$2,$3)
ON CONFLICT (candidate_id, name) DO NOTHING;

-- name: ListCandidateCertifications :many
SELECT name FROM candidate_certifications WHERE candidate_id = $1 ORDER BY name;

-- name: AddCandidateCustomerExperience :exec
INSERT INTO candidate_customer_experience (organization_id, candidate_id, agency)
VALUES ($1,$2,$3)
ON CONFLICT (candidate_id, agency) DO NOTHING;

-- name: ListCandidateCustomerExperience :many
SELECT agency FROM candidate_customer_experience WHERE candidate_id = $1 ORDER BY agency;

-- name: SearchCandidatesHybrid :many
-- Hybrid retrieval: pgvector cosine kNN fused with full-text rank via Reciprocal Rank Fusion (k=60).
-- RLS already scopes both legs to the caller's org. $1=query embedding, $2=limit, $3=text query.
-- Every ORDER BY carries a unique tiebreaker (id) so results are byte-stable for fixed inputs, the
-- AEDT reproducibility mandate [review SQLC-2/PGV-1/PGV-2]. Caller SETs LOCAL hnsw.ef_search first.
WITH vec AS (
    SELECT id, ROW_NUMBER() OVER (ORDER BY resume_embedding <=> $1::vector, id) AS rnk
    FROM candidates
    WHERE deleted_at IS NULL AND resume_embedding IS NOT NULL
    ORDER BY resume_embedding <=> $1::vector, id
    LIMIT $2
),
fts AS (
    SELECT id, ROW_NUMBER() OVER (
               ORDER BY ts_rank(search_tsv, websearch_to_tsquery('english', $3)) DESC, id
           ) AS rnk
    FROM candidates
    WHERE deleted_at IS NULL AND search_tsv @@ websearch_to_tsquery('english', $3)
    ORDER BY ts_rank(search_tsv, websearch_to_tsquery('english', $3)) DESC, id
    LIMIT $2
)
SELECT c.*,
       (COALESCE(1.0/(60+vec.rnk), 0) + COALESCE(1.0/(60+fts.rnk), 0))::float8 AS rrf_score
FROM candidates c
LEFT JOIN vec ON vec.id = c.id
LEFT JOIN fts ON fts.id = c.id
WHERE (vec.id IS NOT NULL OR fts.id IS NOT NULL) AND c.deleted_at IS NULL
ORDER BY rrf_score DESC, c.created_at DESC, c.id
LIMIT $2;