Datasets:
metadata
id: offline-compute_HiveSQL_hivesql_014
name: >-
Filter add-friend behavior from
internal_platform_db.log_17047_query_engine_102
category: offline-compute/HiveSQL
timeout_seconds: 600
modality: pure-text
engine: hivesql
Prompt
Task Objective: Perform cluster aggregation analysis on add-friend behavior logs to identify malicious clusters, and output statistical metrics for each cluster.
Input:
internal_platform_db.log_17047_query_engine_102(add-friend behavior log table)
Processing Rules:
- No joins, single-table processing, using UNION of two subqueries
- Time filter:
day_between 20260608–20260609,hour_between 2026060823–2026060900,timestamp_between 202606082320 and 202606090020 - Branch 1 filter:
appname_ in ('app_hello_txt', 'app_add_contact'),uinregcountry_ in ('CN','HK','MO'),touinregcountry_='CN',length(headmd5_)>0,commfrinum_=0 - Branch 2 filter:
appname_='app_contact_verify_ok',uinregcountry_ in ('CN','HK','MO'),touinregcountry_='CN',commfrinum_=0 - Grouping fields:
appname_,clientversion_,scene_,ticketscene_,headmd5_(empty string for branch 2),uinipcountryid_,uinipprovinceid_ - Aggregation fields:
addfri_pv=count(*),user_id_cnt=count(distinct user_id_),low_quality_cnt=sum(if(uinhighquality_=0,1,0)),low_quality_rate=low_quality_cnt/addfri_pv,user_id_list=concat_ws(',',collect_set(cast(user_id_ as string))),hello_content_list=concat_ws('|',collect_set(content_)),evil_cnt=sum(if(uinlastunbantime_>0 or opentime_+86400*90>timestamp_ or friendnum_<10,1,0)),evil_rate=evil_cnt/addfri_pv - HAVING filter:
user_id_cnt>20AND (low_quality_rate>0.99ORevil_rate>0.98)
Output Requirements:
Field order: appname_, clientversion_, scene_, ticketscene_, headmd5_, uinipcountryid_, uinipprovinceid_, addfri_pv, user_id_cnt, low_quality_cnt, low_quality_rate, user_id_list, hello_content_list, evil_cnt, evil_rate
Write Requirements:
INSERT INTO internal_platform_db.t_acct_addfri_action_cluster_minutely_cand_query_engine_102 PARTITION(ds=202606090010)
Please write the final HiveSQL to result.sql and execute it.