def ZJ_RUN_DETECT_EXEC_MODEL(db_name_ ,dbid_ ,inst_id_ ,gath_time):
gath_time_= datetime.datetime.strptime(gath_time.encode('utf-8').decode("utf-8"), "%Y-%m-%d %H:%M")
print("exec detect gath_time_ %s" %gath_time_)
logger = top_log()
try:
conn = database_method.initial_connect('dmuser', 'dmuser', 'dmtest')
conn = conn.create_conn()
cursor = conn.cursor()
cursor.callproc('ZJ_RUN_DETECT_EXEC_MODEL', [db_name_, dbid_,inst_id_,gath_time_])
conn.commit()
cursor.close()
conn.close()
except Exception as msg:
logger.info(msg)
def home(request):
# return render(request,'home.html')
# if request.method == 'POST':
# username = request.POST.get('username',None)
# age = request.POST.get("age",None)
# gender = request.POST.get("gender",None)
# usergroup_id = request.POST.get("group",None)
# models.UserInfo.objects.create(username=username, age=age, gender=gender,usergroup_id=usergroup_id)
# USER_LIST = list(models.UserInfo.objects.all())
# return render(request,"./node_modules/gentelella/production/anom_total.html",{"userlist":USER_LIST})
conn = database_method.initial_connect('dmuser', 'dmuser', 'dmtest')
conn = conn.create_conn()
cursor = conn.cursor()
cpu_outlier_result = """
select "TIME",
"SNAP_ID",
"DB_CPU",
db_id,
'/ora_dual/load_profile_trend/?snapid='||SNAP_ID||'&dbid='||db_id
from (
SELECT
"TIME",
"SNAP_ID",
"DB_CPU",
db_id,
PREDICTION_PROBABILITY(dmuser.ANOM_SVM_1_6 USING *) ANOM_SVM_1_6_PROB,
PREDICTION(dmuser.ANOM_SVM_1_6 USING *) ANOM_SVM_1_6_PRED
FROM dmuser.stat_all_pivot_data) where ANOM_SVM_1_6_PRED=1 and rownum=1
"""
sql_outlier_result = """
select * from (
select type
from topsql_all_data_his_view
)
pivot
(
count(*)
for type in ('CPU Time' as "CPU_TIME",'Elapse Time' as "ELAPSE_TIME",'Buffer Reads' as "BUFFER_READS",'Physical Reads' as "PHYSICAL_READS",'Executions' as "EXECUTIONS")
)
"""
cpu_result = """
select db_cpu,time from dmuser.stat_all_pivot_data
"""
# 执行异常探测
cursor.callproc('dmuser.cpu_outlier_apply_model')
# 执行异常分析
cursor.execute(cpu_outlier_result)
data_result_ = cursor.fetchall()
data_result = list(data_result_)
cursor.execute(sql_outlier_result)
sql_result_ = cursor.fetchall()
sql_result = list(sql_result_)
outlier_sql = []
for idx in range(len(sql_result)):
outlier_sql.append({
'CPU': sql_result[idx][0],
'ELA': sql_result[idx][1],
'BUFFER': sql_result[idx][2],
'READ': sql_result[idx][3],
'EXE': sql_result[idx][4]
})
# 提取异常原因
reasons = []
for idx in range(len(data_result)):
url = []
# reason_sql = """
# select extractValue(value(reason_name),('//Attribute/@name'))
# from
# (
# select FEATURE_DETAILS(dmuser.feat_pca_1_6, 1, 10 USING *) data
# from dmuser.stat_all_pivot_data
# where snap_id =
# """ + str(data_result[idx][1]) + """ ) t,TABLE(XMLSequence(Extract(t.data,'//Attribute'))) reason_name where rownum<4
# """
reason_sql = """
select stat_name from (
select * from DBA_HIST_SYS_TIME_MODEL where snap_id=""" + str(
data_result[idx]
[1]) + """ and stat_name not in ('DB time','DB CPU')
order by value desc) where rownum < 4
"""
cursor.execute(reason_sql)
reason_result_ = cursor.fetchall()
for reaon_idx in range(len(reason_result_)):
url.append(
data_result[idx][4] + "&reason=" +
str(reason_result_[reaon_idx]).upper().replace(' ', '_').
replace('(', '').replace(')', '').replace(',', '').replace(
'[', '').replace(']', '').replace('''''', ''))
# url.append(data_result[idx][4] + "&reason=" + str(reason_result_[reaon_idx]))
reasons.append({
"TIME": data_result[idx][0],
"snap_id": data_result[idx][1],
"DB_CPU": data_result[idx][2],
"URL": url,
"reason": reason_result_
})
cursor.execute(cpu_result)
cpu_all_result_ = cursor.fetchall()
cpu_all_result = list(cpu_all_result_)
normal = []
normal_tiem = []
outlier = []
outlier_time = []
timeid = []
for idx_1 in range(len(cpu_all_result)):
# outlier.append({'time':cpu_all_result[idx_1][0],'ANOM_SVM_1_6_PROB':cpu_all_result[idx_1][3]})
outlier.append(cpu_all_result[idx_1][0])
outlier_time.append(cpu_all_result[idx_1][1])
# else:
# #normal.append({'time':cpu_all_result[idx_1][0],'ANOM_SVM_1_6_PROB':cpu_all_result[idx_1][3]})
# normal.append( cpu_all_result[idx_1][3])
# normal_tiem.append(cpu_all_result[idx_1][0])
template = loader.get_template(
'./node_modules/gentelella/production/anom_total.html')
timeline = Timeline(is_auto_play=True, timeline_bottom=0)
cpu_line = Line(title_pos='center')
# cpu_line.add(
# "正常值",
# normal_tiem,
# normal,
# is_smooth=True,
# mark_point=["max", "min"],
# mark_line=["average"],
# legend_top = "50%"
# )
cpu_line.add("DB_CPU",
outlier_time,
outlier,
is_smooth=True,
mark_point=["max", "min"],
mark_line=["average"])
context = dict(
# title = [],
cpu_line=cpu_line.render_embed(),
data_result=reasons,
sql_result=outlier_sql,
# metric_data = load_profile_per_hour,
myechart=timeline.render_embed(),
# host=DEFAULT_HOST,#这句改为下面这句
host=REMOTE_HOST, # <-----修改为这个
script_list=timeline.get_js_dependencies())
return HttpResponse(template.render(context, request))
# return render(request, "./node_modules/gentelella/production/sel_cpuoutlier_data.html", {'data_result': data_result})
cursor.close()
def get_top_sql(i,gath_time):
logger = top_log()
gath_time_ = datetime.datetime.strptime(gath_time.encode('utf-8').decode("utf-8"), "%Y-%m-%d %H:%M")
print("begin gath time:%s" %gath_time_)
try:
conn = database_method.initial_connect('dmuser', 'dmuser', 'dmtest')
conn = conn.create_conn()
if i == 0:
top_sql = """
select a.*
from
(select inst_id as inst_id,
row_number() over (partition by inst_id order by cpu_time desc) as rc,
row_number() over (partition by inst_id order by disk_reads desc) as rr,
row_number() over (partition by inst_id order by elapsed_Time desc) as rt,
row_number() over (partition by inst_id order by BUFFER_GETS desc) as bf,
PARSING_SCHEMA_NAME db_USER,
sql_id,
round(cpu_time/1e6) as cpu_s ,
round(elapsed_Time/1e6) as elap_s ,
round((elapsed_Time - cpu_time)/1e6) wait_s,
trunc((elapsed_Time - cpu_time)*100/greatest(elapsed_Time,1),1)||'%' as "wait/elap",
executions as execs,
round(elapsed_Time/(executions+1)/1e6,2) ela_Pe,
buffer_gets as tot_bufs,
round(buffer_gets/greatest(executions,1),1) as avg_buf,
disk_reads as reads,
round(USER_IO_WAIT_TIME/1e6) as IOwait_s,
(select distinct name from gv$database) as db_name,
(select distinct dbid from gv$database) as dbid,
plan_hash_value
from gv$sqlarea t
where PARSING_SCHEMA_NAME in ('DMUSER')
) a
where rc <=5 or rr<=5 or rt<=5 or bf<=5
order by inst_id,rc
"""
else:
top_sql = """
select a.*
from
(select inst_id as inst_id,
row_number() over (partition by inst_id order by cpu_time desc) as rc,
row_number() over (partition by inst_id order by disk_reads desc) as rr,
row_number() over (partition by inst_id order by elapsed_Time desc) as rt,
row_number() over (partition by inst_id order by BUFFER_GETS desc) as bf,
PARSING_SCHEMA_NAME db_USER,
sql_id,
round(cpu_time/1e6) as cpu_s ,
round(elapsed_Time/1e6) as elap_s ,
round((elapsed_Time - cpu_time)/1e6) wait_s,
trunc((elapsed_Time - cpu_time)*100/greatest(elapsed_Time,1),1)||'%' as "wait/elap",
executions as execs,
round(elapsed_Time/(executions+1)/1e6,2) ela_Pe,
buffer_gets as tot_bufs,
round(buffer_gets/greatest(executions,1),1) as avg_buf,
disk_reads as reads,
round(USER_IO_WAIT_TIME/1e6) as IOwait_s,
(select distinct name from gv$database) as db_name,
(select distinct dbid from gv$database) as dbid,
plan_hash_value
from gv$sqlarea t
where PARSING_SCHEMA_NAME not in ('SYS','SYSTEM','DBSNMP','DMUSER','MDSYS','ODMRSYS')
) a
where rc <=5 or rr<=5 or rt<=5 or bf<=5
order by inst_id,rc
"""
cursor = conn.cursor()
cursor.execute(top_sql)
top_sql_data = cursor.fetchall()
result = []
for j in range(len(top_sql_data)):
result.append((gath_time_,top_sql_data[j][17],top_sql_data[j][18],top_sql_data[j][0],top_sql_data[j][5],top_sql_data[j][6],top_sql_data[j][19],top_sql_data[j][7],top_sql_data[j][8],top_sql_data[j][9],top_sql_data[j][11],top_sql_data[j][13],top_sql_data[j][15]))
cursor.prepare(
"insert into top_sql_data(GATH_TIME,DB_NAME,dbid,INST_ID,PARSING_SCHEMA_NAME,SQL_ID,plan_hash_value,cpu_s,elap_s,wait_s,EXECS,BUFFERS,DISK_READS) values(:1,:2,:3,:4,:5,:6,:7,:8,:9,:10,:11,:12,:13)")
#print(result)
cursor.executemany(None, result)
cursor.callproc('ZJ_PRE_DEAL_SQLDATA', [gath_time_,'DMTEST', top_sql_data[j][18],top_sql_data[j][0]])
#
conn.commit()
cursor.close()
conn.close()
#contert_to_json(top_sql_data,top_ash_data)
#logger.info(top_sql_data)
#print(top_sql_data)
except Exception as msg:
logger.info(msg)
