diff --git a/api/chalicelib/core/significance.py b/api/chalicelib/core/significance.py index 1522dc94a..21e701157 100644 --- a/api/chalicelib/core/significance.py +++ b/api/chalicelib/core/significance.py @@ -189,9 +189,10 @@ def get_stages_and_events(filter_d, project_id) -> List[RealDictRow]: {(" AND " + " AND ".join(stage_constraints)) if len(stage_constraints) > 0 else ""} {(" AND " + " AND ".join(first_stage_extra_constraints)) if len(first_stage_extra_constraints) > 0 and i == 0 else ""} GROUP BY main.session_id) - AS T{i + 1} {"USING (session_id)" if i > 0 else ""} + AS T{i + 1} {"ON (TRUE)" if i > 0 else ""} """) - if len(n_stages_query) == 0: + n_stages=len(n_stages_query) + if n_stages == 0: return [] n_stages_query = " LEFT JOIN LATERAL ".join(n_stages_query) n_stages_query += ") AS stages_t" @@ -200,20 +201,20 @@ def get_stages_and_events(filter_d, project_id) -> List[RealDictRow]: SELECT stages_and_issues_t.*, sessions.user_uuid FROM ( SELECT * FROM ( - SELECT * FROM - {n_stages_query} + SELECT T1.session_id, {",".join([f"stage{i + 1}_timestamp" for i in range(n_stages)])} + FROM {n_stages_query} LEFT JOIN LATERAL - ( SELECT ISE.session_id, - ISS.type as issue_type, + ( SELECT ISS.type as issue_type, ISE.timestamp AS issue_timestamp, - ISS.context_string as issue_context, + COALESCE(ISS.context_string,'') as issue_context, ISS.issue_id as issue_id FROM events_common.issues AS ISE INNER JOIN issues AS ISS USING (issue_id) WHERE ISE.timestamp >= stages_t.stage1_timestamp AND ISE.timestamp <= stages_t.stage{i + 1}_timestamp AND ISS.project_id=%(project_id)s + AND ISE.session_id = stages_t.session_id {"AND ISS.type IN %(issueTypes)s" if len(filter_issues) > 0 else ""} - ) AS issues_t USING (session_id) + ) AS issues_t ON (TRUE) ) AS stages_and_issues_t INNER JOIN sessions USING(session_id); """ @@ -345,12 +346,10 @@ def get_transitions_and_issues_of_each_type(rows: List[RealDictRow], all_issues, if error_id not in errors: errors[error_id] = [] ic = 0 - issue_type = all_issues[error_id]["issue_type"] - context = all_issues[error_id]["context"] - if row['issue_type'] is not None: + row_issue_id=row['issue_id'] + if row_issue_id is not None: if last_ts is None or (first_ts < row['issue_timestamp'] < last_ts): - context_in_row = row['issue_context'] if row['issue_context'] is not None else '' - if issue_type == row['issue_type'] and context == context_in_row: + if error_id == row_issue_id: ic = 1 ic_present = True errors[error_id].append(ic) @@ -391,9 +390,8 @@ def get_affected_users_for_all_issues(rows, first_stage, last_stage): # check that the issue exists and belongs to subfunnel: if iss is not None and (row[f'stage{last_stage}_timestamp'] is None or (row[f'stage{first_stage}_timestamp'] < iss_ts < row[f'stage{last_stage}_timestamp'])): - context_string = row['issue_context'] if row['issue_context'] is not None else '' if row["issue_id"] not in all_issues: - all_issues[row["issue_id"]] = {"context": context_string, "issue_type": row["issue_type"]} + all_issues[row["issue_id"]] = {"context": row['issue_context'], "issue_type": row["issue_type"]} n_issues_dict[row["issue_id"]] += 1 if row['user_uuid'] is not None: affected_users[row["issue_id"]].add(row['user_uuid']) diff --git a/ee/api/chalicelib/core/significance.py b/ee/api/chalicelib/core/significance.py index 59f773c9e..b669be2fb 100644 --- a/ee/api/chalicelib/core/significance.py +++ b/ee/api/chalicelib/core/significance.py @@ -188,9 +188,7 @@ def get_stages_and_events(filter_d, project_id) -> List[RealDictRow]: values=s["value"], value_key=f"value{i + 1}") n_stages_query.append(f""" (SELECT main.session_id, - {"MIN(main.timestamp)" if i + 1 < len(stages) else "MAX(main.timestamp)"} AS stage{i + 1}_timestamp, - '{event_type}' AS type, - '{s["operator"]}' AS operator + {"MIN(main.timestamp)" if i + 1 < len(stages) else "MAX(main.timestamp)"} AS stage{i + 1}_timestamp FROM {next_table} AS main {" ".join(extra_from)} WHERE main.timestamp >= {f"T{i}.stage{i}_timestamp" if i > 0 else "%(startTimestamp)s"} {f"AND main.session_id=T1.session_id" if i > 0 else ""} @@ -198,45 +196,53 @@ def get_stages_and_events(filter_d, project_id) -> List[RealDictRow]: {(" AND " + " AND ".join(stage_constraints)) if len(stage_constraints) > 0 else ""} {(" AND " + " AND ".join(first_stage_extra_constraints)) if len(first_stage_extra_constraints) > 0 and i == 0 else ""} GROUP BY main.session_id) - AS T{i + 1} {"USING (session_id)" if i > 0 else ""} + AS T{i + 1} {"ON (TRUE)" if i > 0 else ""} """) - if len(n_stages_query) == 0: + n_stages=len(n_stages_query) + if n_stages == 0: return [] n_stages_query = " LEFT JOIN LATERAL ".join(n_stages_query) n_stages_query += ") AS stages_t" n_stages_query = f""" - SELECT stages_and_issues_t.*,sessions.session_id, sessions.user_uuid FROM ( + SELECT stages_and_issues_t.*, sessions.user_uuid + FROM ( SELECT * FROM ( - SELECT * FROM - {n_stages_query} + SELECT T1.session_id, {",".join([f"stage{i + 1}_timestamp" for i in range(n_stages)])} + FROM {n_stages_query} LEFT JOIN LATERAL - ( - SELECT * FROM - (SELECT ISE.session_id, - ISS.type as issue_type, + ( SELECT ISS.type as issue_type, ISE.timestamp AS issue_timestamp, - ISS.context_string as issue_context, + COALESCE(ISS.context_string,'') as issue_context, ISS.issue_id as issue_id FROM events_common.issues AS ISE INNER JOIN issues AS ISS USING (issue_id) WHERE ISE.timestamp >= stages_t.stage1_timestamp AND ISE.timestamp <= stages_t.stage{i + 1}_timestamp AND ISS.project_id=%(project_id)s - {"AND ISS.type IN %(issueTypes)s" if len(filter_issues) > 0 else ""}) AS base_t - ) AS issues_t - USING (session_id)) AS stages_and_issues_t - inner join sessions USING(session_id); + AND ISE.session_id = stages_t.session_id + {"AND ISS.type IN %(issueTypes)s" if len(filter_issues) > 0 else ""} + ) AS issues_t ON (TRUE) + ) AS stages_and_issues_t INNER JOIN sessions USING(session_id); """ # LIMIT 10000 params = {"project_id": project_id, "startTimestamp": filter_d["startDate"], "endTimestamp": filter_d["endDate"], "issueTypes": tuple(filter_issues), **values} with pg_client.PostgresClient() as cur: + query = cur.mogrify(n_stages_query, params) # print("---------------------------------------------------") - # print(cur.mogrify(n_stages_query, params)) + # print(query) # print("---------------------------------------------------") - cur.execute(cur.mogrify(n_stages_query, params)) - rows = cur.fetchall() + try: + cur.execute(query) + rows = cur.fetchall() + except Exception as err: + print("--------- FUNNEL SEARCH QUERY EXCEPTION -----------") + print(query.decode('UTF-8')) + print("--------- PAYLOAD -----------") + print(filter_d) + print("--------------------") + raise err return rows @@ -298,7 +304,21 @@ def pearson_corr(x: list, y: list): return r, confidence, False -def get_transitions_and_issues_of_each_type(rows: List[RealDictRow], all_issues_with_context, first_stage, last_stage): +# def tuple_or(t: tuple): +# x = 0 +# for el in t: +# x |= el # | is for bitwise OR +# return x +# +# The following function is correct optimization of the previous function because t is a list of 0,1 +def tuple_or(t: tuple): + for el in t: + if el > 0: + return 1 + return 0 + + +def get_transitions_and_issues_of_each_type(rows: List[RealDictRow], all_issues, first_stage, last_stage): """ Returns two lists with binary values 0/1: @@ -317,12 +337,6 @@ def get_transitions_and_issues_of_each_type(rows: List[RealDictRow], all_issues_ transitions = [] n_sess_affected = 0 errors = {} - for issue in all_issues_with_context: - split = issue.split('__^__') - errors[issue] = { - "errors": [], - "issue_type": split[0], - "context": split[1]} for row in rows: t = 0 @@ -330,38 +344,28 @@ def get_transitions_and_issues_of_each_type(rows: List[RealDictRow], all_issues_ last_ts = row[f'stage{last_stage}_timestamp'] if first_ts is None: continue - elif first_ts is not None and last_ts is not None: + elif last_ts is not None: t = 1 transitions.append(t) ic_present = False - for issue_type_with_context in errors: + for error_id in all_issues: + if error_id not in errors: + errors[error_id] = [] ic = 0 - issue_type = errors[issue_type_with_context]["issue_type"] - context = errors[issue_type_with_context]["context"] + issue_type = all_issues[error_id]["issue_type"] + context = all_issues[error_id]["context"] if row['issue_type'] is not None: if last_ts is None or (first_ts < row['issue_timestamp'] < last_ts): context_in_row = row['issue_context'] if row['issue_context'] is not None else '' if issue_type == row['issue_type'] and context == context_in_row: ic = 1 ic_present = True - errors[issue_type_with_context]["errors"].append(ic) + errors[error_id].append(ic) if ic_present and t: n_sess_affected += 1 - # def tuple_or(t: tuple): - # x = 0 - # for el in t: - # x |= el - # return x - def tuple_or(t: tuple): - for el in t: - if el > 0: - return 1 - return 0 - - errors = {key: errors[key]["errors"] for key in errors} all_errors = [tuple_or(t) for t in zip(*errors.values())] return transitions, errors, all_errors, n_sess_affected @@ -377,10 +381,9 @@ def get_affected_users_for_all_issues(rows, first_stage, last_stage): """ affected_users = defaultdict(lambda: set()) affected_sessions = defaultdict(lambda: set()) - contexts = defaultdict(lambda: None) + all_issues = {} n_affected_users_dict = defaultdict(lambda: None) n_affected_sessions_dict = defaultdict(lambda: None) - all_issues_with_context = set() n_issues_dict = defaultdict(lambda: 0) issues_by_session = defaultdict(lambda: 0) @@ -397,14 +400,13 @@ def get_affected_users_for_all_issues(rows, first_stage, last_stage): if iss is not None and (row[f'stage{last_stage}_timestamp'] is None or (row[f'stage{first_stage}_timestamp'] < iss_ts < row[f'stage{last_stage}_timestamp'])): context_string = row['issue_context'] if row['issue_context'] is not None else '' - issue_with_context = iss + '__^__' + context_string - contexts[issue_with_context] = {"context": context_string, "id": row["issue_id"]} - all_issues_with_context.add(issue_with_context) - n_issues_dict[issue_with_context] += 1 + if row["issue_id"] not in all_issues: + all_issues[row["issue_id"]] = {"context": context_string, "issue_type": row["issue_type"]} + n_issues_dict[row["issue_id"]] += 1 if row['user_uuid'] is not None: - affected_users[issue_with_context].add(row['user_uuid']) + affected_users[row["issue_id"]].add(row['user_uuid']) - affected_sessions[issue_with_context].add(row['session_id']) + affected_sessions[row["issue_id"]].add(row['session_id']) issues_by_session[row[f'session_id']] += 1 if len(affected_users) > 0: @@ -415,29 +417,28 @@ def get_affected_users_for_all_issues(rows, first_stage, last_stage): n_affected_sessions_dict.update({ iss: len(affected_sessions[iss]) for iss in affected_sessions }) - return all_issues_with_context, n_issues_dict, n_affected_users_dict, n_affected_sessions_dict, contexts + return all_issues, n_issues_dict, n_affected_users_dict, n_affected_sessions_dict def count_sessions(rows, n_stages): session_counts = {i: set() for i in range(1, n_stages + 1)} - for ind, row in enumerate(rows): + for row in rows: for i in range(1, n_stages + 1): if row[f"stage{i}_timestamp"] is not None: session_counts[i].add(row[f"session_id"]) + session_counts = {i: len(session_counts[i]) for i in session_counts} return session_counts def count_users(rows, n_stages): - users_in_stages = defaultdict(lambda: set()) - - for ind, row in enumerate(rows): + users_in_stages = {i: set() for i in range(1, n_stages + 1)} + for row in rows: for i in range(1, n_stages + 1): if row[f"stage{i}_timestamp"] is not None: users_in_stages[i].add(row["user_uuid"]) users_count = {i: len(users_in_stages[i]) for i in range(1, n_stages + 1)} - return users_count @@ -490,18 +491,18 @@ def get_issues(stages, rows, first_stage=None, last_stage=None, drop_only=False) last_stage = n_stages n_critical_issues = 0 - issues_dict = dict({"significant": [], - "insignificant": []}) + issues_dict = {"significant": [], + "insignificant": []} session_counts = count_sessions(rows, n_stages) drop = session_counts[first_stage] - session_counts[last_stage] - all_issues_with_context, n_issues_dict, affected_users_dict, affected_sessions, contexts = get_affected_users_for_all_issues( + all_issues, n_issues_dict, affected_users_dict, affected_sessions = get_affected_users_for_all_issues( rows, first_stage, last_stage) transitions, errors, all_errors, n_sess_affected = get_transitions_and_issues_of_each_type(rows, - all_issues_with_context, + all_issues, first_stage, last_stage) - # print("len(transitions) =", len(transitions)) + del rows if any(all_errors): total_drop_corr, conf, is_sign = pearson_corr(transitions, all_errors) @@ -514,33 +515,32 @@ def get_issues(stages, rows, first_stage=None, last_stage=None, drop_only=False) if drop_only: return total_drop_due_to_issues - for issue in all_issues_with_context: + for issue_id in all_issues: - if not any(errors[issue]): + if not any(errors[issue_id]): continue - r, confidence, is_sign = pearson_corr(transitions, errors[issue]) + r, confidence, is_sign = pearson_corr(transitions, errors[issue_id]) if r is not None and drop is not None and is_sign: - lost_conversions = int(r * affected_sessions[issue]) + lost_conversions = int(r * affected_sessions[issue_id]) else: lost_conversions = None if r is None: r = 0 - split = issue.split('__^__') issues_dict['significant' if is_sign else 'insignificant'].append({ - "type": split[0], - "title": helper.get_issue_title(split[0]), - "affected_sessions": affected_sessions[issue], - "unaffected_sessions": session_counts[1] - affected_sessions[issue], + "type": all_issues[issue_id]["issue_type"], + "title": helper.get_issue_title(all_issues[issue_id]["issue_type"]), + "affected_sessions": affected_sessions[issue_id], + "unaffected_sessions": session_counts[1] - affected_sessions[issue_id], "lost_conversions": lost_conversions, - "affected_users": affected_users_dict[issue], + "affected_users": affected_users_dict[issue_id], "conversion_impact": round(r * 100), - "context_string": contexts[issue]["context"], - "issue_id": contexts[issue]["id"] + "context_string": all_issues[issue_id]["context"], + "issue_id": issue_id }) if is_sign: - n_critical_issues += n_issues_dict[issue] + n_critical_issues += n_issues_dict[issue_id] return n_critical_issues, issues_dict, total_drop_due_to_issues