refs #737: move game query planning into ADB MCP tool
This commit is contained in:
devmrko
194
sql/adb/81_sg_game_query_plan.sql
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194
sql/adb/81_sg_game_query_plan.sql
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-- OCI GenAI candidate selection. Vector distance only orders candidates; the
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-- model may select one supplied game_key or explicitly reject all candidates.
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CREATE OR REPLACE FUNCTION sg_game_match_candidate(
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p_mention IN CLOB,
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p_candidates_json IN CLOB
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) RETURN CLOB AUTHID DEFINER
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IS
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v_prompt CLOB;
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v_result CLOB;
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BEGIN
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v_prompt := 'Decide whether the extracted game-name mention refers to exactly '
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|| 'one game in the supplied candidate array. Candidate vector distance is '
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|| 'retrieval evidence only and must not establish identity. Compare the '
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|| 'mention with candidate gameName, aliases, gameId, and gamePrefix. '
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|| 'If one candidate clearly identifies the same game, return exactly '
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|| '{"status":"MATCHED","game_key":"candidate key","reason":"short reason"}. '
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|| 'If none clearly identifies the same game, return exactly '
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|| '{"status":"UNMATCHED","game_key":null,"reason":"short reason"}. '
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|| 'Never invent a game_key and never return a key absent from the supplied '
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|| 'candidate array. Mention: '
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|| DBMS_LOB.SUBSTR(p_mention, 1000, 1)
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|| ' Candidates: '
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|| DBMS_LOB.SUBSTR(p_candidates_json, 12000, 1);
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v_result := DBMS_CLOUD_AI.GENERATE(
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prompt => v_prompt,
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profile_name => 'SGMP_POC_OCI_GPT54MINI',
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action => 'chat'
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);
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RETURN v_result;
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END;
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/
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-- Complete game query planning inside ADB. The MCP server only invokes this
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-- function and returns its structured result.
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CREATE OR REPLACE FUNCTION sg_game_query_plan(
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p_question IN CLOB,
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p_top_k IN PLS_INTEGER DEFAULT 5
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) RETURN CLOB AUTHID DEFINER
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IS
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TYPE t_seen_game_keys IS TABLE OF BOOLEAN INDEX BY VARCHAR2(128);
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v_extract_raw CLOB;
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v_extract JSON_OBJECT_T;
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v_mentions JSON_ARRAY_T;
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v_scope_type VARCHAR2(30);
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v_supported JSON_ARRAY_T := JSON_ARRAY_T();
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v_unmatched JSON_ARRAY_T := JSON_ARRAY_T();
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v_mention_results JSON_ARRAY_T := JSON_ARRAY_T();
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v_seen_game_keys t_seen_game_keys;
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v_result JSON_OBJECT_T := JSON_OBJECT_T();
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v_mention VARCHAR2(1000);
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v_candidates JSON_ARRAY_T;
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v_candidate JSON_OBJECT_T;
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v_decision_raw CLOB;
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v_decision JSON_OBJECT_T;
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v_decision_status VARCHAR2(30);
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v_selected_key VARCHAR2(128);
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v_reason VARCHAR2(4000);
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v_matched_candidate JSON_OBJECT_T;
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v_mention_result JSON_OBJECT_T;
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v_unmatched_item JSON_OBJECT_T;
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v_cursor SYS_REFCURSOR;
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v_game_key VARCHAR2(128);
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v_game_id VARCHAR2(128);
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v_game_prefix VARCHAR2(128);
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v_game_nm VARCHAR2(512);
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v_game_alias_nm VARCHAR2(512);
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v_cosine_distance NUMBER;
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BEGIN
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v_extract_raw := sg_game_extract_mentions(p_question);
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v_extract := JSON_OBJECT_T.parse(v_extract_raw);
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v_mentions := v_extract.get_array('game_mentions');
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v_scope_type := NVL(v_extract.get_string('scope_hint'), 'UNKNOWN');
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FOR i IN 0 .. v_mentions.get_size - 1 LOOP
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v_mention := v_mentions.get_string(i);
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v_candidates := JSON_ARRAY_T();
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v_cursor := sg_game_catalog_search(
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v_mention,
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LEAST(GREATEST(NVL(p_top_k, 5), 1), 20)
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);
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LOOP
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FETCH v_cursor INTO
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v_game_key,
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v_game_id,
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v_game_prefix,
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v_game_nm,
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v_game_alias_nm,
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v_cosine_distance;
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EXIT WHEN v_cursor%NOTFOUND;
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v_candidate := JSON_OBJECT_T();
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v_candidate.put('gameKey', v_game_key);
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v_candidate.put('gameId', v_game_id);
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v_candidate.put('gamePrefix', v_game_prefix);
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v_candidate.put('gameName', v_game_nm);
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v_candidate.put('aliases', v_game_alias_nm);
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v_candidate.put('cosineDistance', v_cosine_distance);
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v_candidates.append(v_candidate);
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END LOOP;
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CLOSE v_cursor;
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v_decision_raw := sg_game_match_candidate(
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v_mention,
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v_candidates.to_clob
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);
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v_decision := JSON_OBJECT_T.parse(v_decision_raw);
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v_decision_status := UPPER(
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NVL(v_decision.get_string('status'), 'UNMATCHED')
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);
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v_selected_key := v_decision.get_string('game_key');
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v_reason := v_decision.get_string('reason');
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v_matched_candidate := NULL;
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IF v_decision_status = 'MATCHED' AND v_selected_key IS NOT NULL THEN
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FOR j IN 0 .. v_candidates.get_size - 1 LOOP
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v_candidate := TREAT(v_candidates.get(j) AS JSON_OBJECT_T);
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IF v_candidate.get_string('gameKey') = v_selected_key THEN
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v_matched_candidate := v_candidate;
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EXIT;
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END IF;
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END LOOP;
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END IF;
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v_mention_result := JSON_OBJECT_T();
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v_mention_result.put('mention', v_mention);
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v_mention_result.put('candidateGames', v_candidates);
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v_mention_result.put('reason', v_reason);
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IF v_matched_candidate IS NOT NULL THEN
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v_mention_result.put('status', 'MATCHED');
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v_mention_result.put('reasonCode', 'LLM_CANDIDATE_MATCH');
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v_mention_result.put('matchedGameKey', v_selected_key);
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IF NOT v_seen_game_keys.EXISTS(v_selected_key) THEN
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v_supported.append(v_matched_candidate);
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v_seen_game_keys(v_selected_key) := TRUE;
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END IF;
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ELSE
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v_mention_result.put('status', 'UNMATCHED');
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IF v_decision_status = 'MATCHED' THEN
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v_mention_result.put(
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'reasonCode',
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'LLM_SELECTED_UNKNOWN_CANDIDATE'
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);
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ELSE
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v_mention_result.put('reasonCode', 'LLM_NO_CANDIDATE_MATCH');
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END IF;
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v_unmatched_item := JSON_OBJECT_T();
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v_unmatched_item.put('mention', v_mention);
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v_unmatched_item.put(
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'reasonCode',
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v_mention_result.get_string('reasonCode')
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);
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v_unmatched_item.put('reason', v_reason);
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v_unmatched.append(v_unmatched_item);
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END IF;
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v_mention_results.append(v_mention_result);
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END LOOP;
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v_result.put('scopeType', v_scope_type);
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IF v_supported.get_size = 0 THEN
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v_result.put('status', 'NO_MATCH');
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ELSIF v_unmatched.get_size > 0 THEN
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v_result.put('status', 'PARTIAL');
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ELSE
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v_result.put('status', 'SUPPORTED');
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END IF;
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v_result.put('matchedGames', v_supported);
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v_result.put('mentionResults', v_mention_results);
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v_result.put('supportedGames', v_supported);
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v_result.put('unmatchedGames', v_unmatched);
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IF v_supported.get_size = 0 THEN
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v_result.put('nextAction', 'STOP_NO_MATCH');
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ELSIF v_scope_type = 'MULTI_GAME' THEN
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v_result.put('nextAction', 'CALL_FEWSHOT_PER_GAME');
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ELSE
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v_result.put('nextAction', 'CALL_FEWSHOT');
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END IF;
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CASE v_scope_type
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WHEN 'SINGLE_GAME' THEN v_result.put('executionMode', 'SINGLE');
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WHEN 'MULTI_GAME' THEN v_result.put('executionMode', 'FAN_OUT');
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WHEN 'ALL_GAMES' THEN v_result.put('executionMode', 'GROUPED');
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ELSE v_result.put('executionMode', 'BLOCKED');
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END CASE;
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RETURN v_result.to_clob;
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END;
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/
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