dataflow/database/functions.sql

--
-- Dataflow Functions
-- Simple, clear functions for import and transformation
--

SET search_path TO dataflow, public;

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-- Function: import_records
-- Import data with automatic deduplication
------------------------------------------------------
CREATE OR REPLACE FUNCTION import_records(
    p_source_name TEXT,
    p_data JSONB  -- Array of records
) RETURNS JSON AS $$
DECLARE
    v_dedup_fields TEXT[];
    v_record JSONB;
    v_dedup_key TEXT;
    v_inserted INTEGER := 0;
    v_duplicates INTEGER := 0;
    v_log_id INTEGER;
BEGIN
    -- Get dedup fields for this source
    SELECT dedup_fields INTO v_dedup_fields
    FROM dataflow.sources
    WHERE name = p_source_name;

    IF v_dedup_fields IS NULL THEN
        RETURN json_build_object(
            'success', false,
            'error', 'Source not found: ' || p_source_name
        );
    END IF;

    -- Process each record
    FOR v_record IN SELECT * FROM jsonb_array_elements(p_data)
    LOOP
        -- Generate dedup key
        v_dedup_key := dataflow.generate_dedup_key(v_record, v_dedup_fields);

        -- Try to insert (will fail silently if duplicate)
        BEGIN
            INSERT INTO dataflow.records (source_name, data, dedup_key)
            VALUES (p_source_name, v_record, v_dedup_key);

            v_inserted := v_inserted + 1;
        EXCEPTION WHEN unique_violation THEN
            v_duplicates := v_duplicates + 1;
        END;
    END LOOP;

    -- Log the import
    INSERT INTO dataflow.import_log (source_name, records_imported, records_duplicate)
    VALUES (p_source_name, v_inserted, v_duplicates)
    RETURNING id INTO v_log_id;

    RETURN json_build_object(
        'success', true,
        'imported', v_inserted,
        'duplicates', v_duplicates,
        'log_id', v_log_id
    );
END;
$$ LANGUAGE plpgsql;

COMMENT ON FUNCTION import_records IS 'Import records with automatic deduplication';

------------------------------------------------------
-- Function: apply_transformations
-- Apply all transformation rules to records
------------------------------------------------------
CREATE OR REPLACE FUNCTION apply_transformations(
    p_source_name TEXT,
    p_record_ids INTEGER[] DEFAULT NULL  -- NULL = all untransformed
) RETURNS JSON AS $$
DECLARE
    v_record RECORD;
    v_rule RECORD;
    v_transformed JSONB;
    v_extracted TEXT;
    v_mapping JSONB;
    v_count INTEGER := 0;
BEGIN
    -- Loop through records to transform
    FOR v_record IN
        SELECT id, data
        FROM dataflow.records
        WHERE source_name = p_source_name
          AND (p_record_ids IS NULL OR id = ANY(p_record_ids))
          AND transformed IS NULL
    LOOP
        -- Start with original data
        v_transformed := v_record.data;

        -- Apply each rule in sequence
        FOR v_rule IN
            SELECT * FROM dataflow.rules
            WHERE source_name = p_source_name
              AND enabled = true
            ORDER BY sequence
        LOOP
            -- Apply rule based on function type
            IF v_rule.function_type = 'replace' THEN
                v_extracted := regexp_replace(
                    v_record.data->>v_rule.field,
                    CASE WHEN v_rule.flags != '' THEN '(?' || v_rule.flags || ')' ELSE '' END || v_rule.pattern,
                    v_rule.output_field
                );
                v_transformed := jsonb_set(
                    v_transformed,
                    ARRAY[v_rule.field],
                    to_jsonb(v_extracted)
                );
            ELSE
                -- extract (default)
                v_extracted := substring(
                    v_record.data->>v_rule.field
                    FROM CASE WHEN v_rule.flags != '' THEN '(?' || v_rule.flags || ')' ELSE '' END || v_rule.pattern
                );

                IF v_extracted IS NOT NULL THEN
                    -- Check if there's a mapping for this value
                    SELECT output INTO v_mapping
                    FROM dataflow.mappings
                    WHERE source_name = p_source_name
                      AND rule_name = v_rule.name
                      AND input_value = v_extracted;

                    IF v_mapping IS NOT NULL THEN
                        -- Apply mapping (merge mapped fields into result)
                        v_transformed := v_transformed || v_mapping;
                    ELSE
                        -- No mapping, just add extracted value
                        v_transformed := jsonb_set(
                            v_transformed,
                            ARRAY[v_rule.output_field],
                            to_jsonb(v_extracted)
                        );
                    END IF;
                END IF;
            END IF;
        END LOOP;

        -- Update record with transformed data
        UPDATE dataflow.records
        SET transformed = v_transformed,
            transformed_at = CURRENT_TIMESTAMP
        WHERE id = v_record.id;

        v_count := v_count + 1;
    END LOOP;

    RETURN json_build_object(
        'success', true,
        'transformed', v_count
    );
END;
$$ LANGUAGE plpgsql;

COMMENT ON FUNCTION apply_transformations IS 'Apply transformation rules and mappings to records';

------------------------------------------------------
-- Function: get_unmapped_values
-- Find extracted values that need mappings
------------------------------------------------------
CREATE OR REPLACE FUNCTION get_unmapped_values(
    p_source_name TEXT,
    p_rule_name TEXT DEFAULT NULL
) RETURNS TABLE (
    rule_name TEXT,
    output_field TEXT,
    extracted_value TEXT,
    record_count BIGINT,
    sample_records JSONB
) AS $$
BEGIN
    RETURN QUERY
    WITH extracted AS (
        SELECT
            r.name AS rule_name,
            r.output_field,
            rec.transformed->>r.output_field AS extracted_value,
            rec.data AS raw_record
        FROM
            dataflow.records rec
            CROSS JOIN dataflow.rules r
        WHERE
            rec.source_name = p_source_name
            AND r.source_name = p_source_name
            AND rec.transformed IS NOT NULL
            AND rec.transformed ? r.output_field
            AND (p_rule_name IS NULL OR r.name = p_rule_name)
    )
    SELECT
        e.rule_name,
        e.output_field,
        e.extracted_value,
        count(*) AS record_count,
        jsonb_agg(e.raw_record ORDER BY e.raw_record) FILTER (WHERE e.raw_record IS NOT NULL) AS sample_records
    FROM (
        SELECT rule_name, output_field, extracted_value, raw_record,
               row_number() OVER (PARTITION BY rule_name, extracted_value ORDER BY (SELECT NULL)) AS rn
        FROM extracted
    ) e
    WHERE NOT EXISTS (
        SELECT 1 FROM dataflow.mappings m
        WHERE m.source_name = p_source_name
          AND m.rule_name = e.rule_name
          AND m.input_value = e.extracted_value
    )
    AND e.rn <= 3
    GROUP BY e.rule_name, e.output_field, e.extracted_value
    ORDER BY count(*) DESC;
END;
$$ LANGUAGE plpgsql;

COMMENT ON FUNCTION get_unmapped_values IS 'Find extracted values that need mappings defined';

------------------------------------------------------
-- Function: reprocess_records
-- Clear and reapply transformations
------------------------------------------------------
CREATE OR REPLACE FUNCTION reprocess_records(p_source_name TEXT)
RETURNS JSON AS $$
BEGIN
    -- Clear existing transformations
    UPDATE dataflow.records
    SET transformed = NULL,
        transformed_at = NULL
    WHERE source_name = p_source_name;

    -- Reapply transformations
    RETURN dataflow.apply_transformations(p_source_name);
END;
$$ LANGUAGE plpgsql;

COMMENT ON FUNCTION reprocess_records IS 'Clear and reapply all transformations for a source';

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-- Summary
------------------------------------------------------
-- Functions: 4 simple, focused functions
--   1. import_records - Import with deduplication
--   2. apply_transformations - Apply rules and mappings
--   3. get_unmapped_values - Find values needing mappings
--   4. reprocess_records - Re-transform all records
--
-- Each function does ONE thing clearly
-- No complex nested CTEs
-- Easy to understand and debug
------------------------------------------------------