未验证 提交 183d9bc4 编写于 作者: H Hui Li 提交者: GitHub

Merge pull request #20662 from taosdata/test/TD-22889-3.0

test : udf for python add ci case udfpy_main.py
......@@ -120,6 +120,7 @@
,,y,system-test,./pytest.sh python3 ./test.py -f 0-others/fsync.py
,,n,system-test,python3 ./test.py -f 0-others/compatibility.py
,,n,system-test,python3 ./test.py -f 0-others/tag_index_basic.py
,,n,system-test,python3 ./test.py -f 0-others/udfpy_main.py
,,y,system-test,./pytest.sh python3 ./test.py -f 1-insert/alter_database.py
,,y,system-test,./pytest.sh python3 ./test.py -f 1-insert/influxdb_line_taosc_insert.py
,,y,system-test,./pytest.sh python3 ./test.py -f 1-insert/opentsdb_telnet_line_taosc_insert.py
......
......@@ -17,6 +17,7 @@ import time
import datetime
import inspect
import importlib
import traceback
from util.log import *
......@@ -75,6 +76,7 @@ class TDCases:
case.run()
except Exception as e:
tdLog.notice(repr(e))
traceback.print_exc()
tdLog.exit("%s failed" % (fileName))
case.stop()
runNum += 1
......
import pickle
def init():
pass
def destroy():
pass
def start():
return pickle.dumps(0)
def finish(buf):
count = pickle.loads(buf)
return count
def reduce(datablock, buf):
(rows, cols) = datablock.shape()
count = pickle.loads(buf)
for i in range(rows):
val = datablock.data(i, 0)
if val is not None:
count += 1
return pickle.dumps(count)
\ No newline at end of file
import pickle
def init():
pass
def destroy():
pass
def start():
return pickle.dumps([])
def finish(buf):
mins = pickle.loads(buf)
min_val = None
for min in mins:
if min_val is None or (min is not None and min < min_val):
min_val = min
return min_val
def reduce(datablock, buf):
(rows, cols) = datablock.shape()
mins = pickle.loads(buf)
min = None
for i in range(rows):
val = datablock.data(i, 0)
if min is None or (val is not None and val < min) :
min = val
if min is not None:
mins.append(min)
return pickle.dumps(mins)
import pickle
def init():
pass
def destroy():
pass
def start():
return pickle.dumps([])
def finish(buf):
return None
def reduce(datablock, buf):
(rows, cols) = datablock.shape()
mins = pickle.loads(buf)
mins.append(None)
return pickle.dumps(mins)
import pickle
def init():
pass
def destroy():
pass
def start():
return pickle.dumps(None)
def finish(buf):
sum = pickle.loads(buf)
return sum
def reduce(datablock, buf):
(rows, cols) = datablock.shape()
sum = pickle.loads(buf)
for i in range(rows):
val = datablock.data(i, 0)
if val is not None:
if sum is None:
sum = val
else:
sum += val
return pickle.dumps(sum)
# init
def init():
pass
# destroy
def destroy():
pass
def process(block):
(nrows, ncols) = block.shape()
results = []
for i in range(nrows):
row = []
for j in range(ncols):
val = block.data(i, j)
if val is None:
row = None
break
row.append(val.decode('utf_32_le'))
if row is None:
results.append(None)
else:
row_str = ''.join(row)
results.append(row_str.encode('utf_32_le'))
return results
# init
def init():
pass
# destroy
def destroy():
pass
def process(block):
(nrows, ncols) = block.shape()
results = []
for i in range(nrows):
row = []
for j in range(ncols):
val = block.data(i, j)
if val is None:
row = None
break
row.append(val.decode('utf-8'))
if row is None:
results.append(None)
else:
results.append(''.join(row))
return results
# init
def init():
pass
# destroy
def destroy():
pass
# return origin column one value
def process(block):
(nrows, ncols) = block.shape()
results = []
for i in range(nrows):
rows = []
for j in range(ncols):
val = block.data(i, j)
if type(val) is bytes:
rows.append(val.decode('utf-8'))
else:
rows.append(repr(val))
results.append(','.join(rows))
return results
# init
def init():
pass
# destroy
def destroy():
pass
# return origin column one value
def process(block):
(rows, cols) = block.shape()
results = []
for i in range(rows):
results.append(None)
return results
\ No newline at end of file
# init
def init():
pass
# destroy
def destroy():
pass
# return origin column one value
def process(block):
(rows, cols) = block.shape()
results = []
for i in range(rows):
results.append(block.data(i,0))
return results
###################################################################
# Copyright (c) 2016 by TAOS Technologies, Inc.
# All rights reserved.
#
# This file is proprietary and confidential to TAOS Technologies.
# No part of this file may be reproduced, stored, transmitted,
# disclosed or used in any form or by any means other than as
# expressly provided by the written permission from Jianhui Tao
#
###################################################################
# -*- coding: utf-8 -*-
from util.log import *
from util.cases import *
from util.sql import *
from util.common import *
from util.sqlset import *
import random
import os
import subprocess
class PerfDB:
def __init__(self):
self.sqls = []
self.spends = []
# execute
def execute(self, sql):
print(f" perfdb execute {sql}")
stime = time.time()
ret = tdSql.execute(sql, 1)
spend = time.time() - stime
self.sqls.append(sql)
self.spends.append(spend)
return ret
# query
def query(self, sql):
print(f" perfdb query {sql}")
start = time.time()
ret = tdSql.query(sql, None, 1)
spend = time.time() - start
self.sqls.append(sql)
self.spends.append(spend)
return ret
class TDTestCase:
def init(self, conn, logSql, replicaVar=1):
self.replicaVar = int(replicaVar)
tdLog.debug("start to execute %s" % __file__)
tdSql.init(conn.cursor())
self.setsql = TDSetSql()
# udf path
self.udf_path = os.path.dirname(os.path.realpath(__file__)) + "/udfpy"
self.column_dict = {
'ts': 'timestamp',
'col1': 'tinyint',
'col2': 'smallint',
'col3': 'int',
'col4': 'bigint',
'col5': 'tinyint unsigned',
'col6': 'smallint unsigned',
'col7': 'int unsigned',
'col8': 'bigint unsigned',
'col9': 'float',
'col10': 'double',
'col11': 'bool',
'col12': 'varchar(120)',
'col13': 'nchar(100)',
}
self.tag_dict = {
't1': 'tinyint',
't2': 'smallint',
't3': 'int',
't4': 'bigint',
't5': 'tinyint unsigned',
't6': 'smallint unsigned',
't7': 'int unsigned',
't8': 'bigint unsigned',
't9': 'float',
't10': 'double',
't11': 'bool',
't12': 'varchar(120)',
't13': 'nchar(100)',
}
def set_stb_sql(self,stbname,column_dict,tag_dict):
column_sql = ''
tag_sql = ''
for k,v in column_dict.items():
column_sql += f"{k} {v}, "
for k,v in tag_dict.items():
tag_sql += f"{k} {v}, "
create_stb_sql = f'create stable {stbname} ({column_sql[:-2]}) tags ({tag_sql[:-2]})'
return create_stb_sql
# create stable and child tables
def create_table(self, stbname, tbname, count):
tdSql.execute("create database db wal_retention_period 4")
tdSql.execute('use db')
self.child_count = count
self.stbname = stbname
self.tbname = tbname
# create stable
create_table_sql = self.set_stb_sql(stbname, self.column_dict, self.tag_dict)
tdSql.execute(create_table_sql)
batch_size = 1000
# create child table
for i in range(count):
ti = i % 128
tags = f'{ti},{ti},{i},{i},{ti},{ti},{i},{i},{i}.000{i},{i}.000{i},true,"var{i}","nch{i}"'
sql = f'create table {tbname}{i} using {stbname} tags({tags});'
tdSql.execute(sql)
if i % batch_size == 0:
tdLog.info(f" create child table {i} ...")
tdLog.info(f" create {count} child tables ok.")
# create with dicts
def create_sf_dicts(self, dicts, filename):
for fun_name, out_type in dicts.items():
sql = f' create function {fun_name} as "{self.udf_path}/{filename}" outputtype {out_type} language "Python" '
tdSql.execute(sql)
tdLog.info(sql)
# create_udfpy_function
def create_scalar_udfpy(self):
# scalar funciton
self.scalar_funs = {
'sf0': 'timestamp',
'sf1': 'tinyint',
'sf2': 'smallint',
'sf3': 'int',
'sf4': 'bigint',
'sf5': 'tinyint unsigned',
'sf6': 'smallint unsigned',
'sf7': 'int unsigned',
'sf8': 'bigint unsigned',
'sf9': 'float',
'sf10': 'double',
'sf11': 'bool',
'sf12': 'varchar(120)',
'sf13': 'nchar(100)'
}
# agg function
self.agg_funs = {
'af1': 'tinyint',
'af2': 'smallint',
'af3': 'int',
'af4': 'bigint',
'af5': 'tinyint unsigned',
'af6': 'smallint unsigned',
'af7': 'int unsigned',
'af8': 'bigint unsigned',
'af9': 'float',
'af10': 'double',
'af11': 'bool',
'af12': 'varchar(120)',
'af13': 'nchar(100)',
'af14': 'timestamp'
}
# multi_args
self.create_sf_dicts(self.scalar_funs, "sf_origin.py")
fun_name = "sf_multi_args"
self.create_udf_sf(fun_name, f'{fun_name}.py', "binary(1024)")
# all type check null
for col_name, col_type in self.column_dict.items():
self.create_udf_sf(f"sf_null_{col_name}", "sf_null.py", col_type)
# concat
fun_name = "sf_concat_var"
self.create_udf_sf(fun_name, f'{fun_name}.py', "varchar(1024)")
fun_name = "sf_concat_nch"
self.create_udf_sf(fun_name, f'{fun_name}.py', "nchar(1024)")
# fun_name == fun_name.py
def create_udf_sf(self, fun_name, file_name, out_type):
sql = f'create function {fun_name} as "{self.udf_path}/{file_name}" outputtype {out_type} language "Python" '
tdSql.execute(sql)
tdLog.info(sql)
def create_udf_af(self, fun_name, file_name, out_type, bufsize):
sql = f'create aggregate function {fun_name} as "{self.udf_path}/{file_name}" outputtype {out_type} bufsize {bufsize} language "Python" '
tdSql.execute(sql)
tdLog.info(sql)
# sql1 query result eual with sql2
def verify_same_result(self, sql1, sql2):
# query
result1 = tdSql.getResult(sql1)
tdSql.query(sql2)
for i, row in enumerate(result1):
for j , val in enumerate(row):
tdSql.checkData(i, j, result1[i][j])
# same value like select col1, udf_fun1(col1) from st
def verify_same_value(self, sql, col=0):
tdSql.query(sql)
nrows = tdSql.getRows()
for i in range(nrows):
val = tdSql.getData(i, col)
tdSql.checkData(i, col + 1, val)
# verify multi values
def verify_same_multi_values(self, sql):
tdSql.query(sql)
nrows = tdSql.getRows()
for i in range(nrows):
udf_val = tdSql.getData(i, 0)
vals = udf_val.split(',')
for j,val in enumerate(vals, 1):
tdSql.checkData(i, j, val)
# query multi-args
def query_multi_args(self):
cols = list(self.column_dict.keys()) + list(self.tag_dict.keys())
cols.remove("col13")
cols.remove("t13")
cols.remove("ts")
ncols = len(cols)
print(cols)
for i in range(2, ncols):
sample = random.sample(cols, i)
print(sample)
cols_name = ','.join(sample)
sql = f'select sf_multi_args({cols_name}),{cols_name} from {self.stbname} limit 10'
self.verify_same_multi_values(sql)
tdLog.info(sql)
# query_udfpy
def query_scalar_udfpy(self):
# col
for col_name, col_type in self.column_dict.items():
for fun_name, out_type in self.scalar_funs.items():
if col_type == out_type :
sql = f'select {col_name}, {fun_name}({col_name}) from {self.stbname} limit 10'
tdLog.info(sql)
self.verify_same_value(sql)
sql = f'select * from (select {col_name} as a, {fun_name}({col_name}) as b from {self.stbname} limit 100) order by b,a desc'
tdLog.info(sql)
self.verify_same_value(sql)
# multi-args
self.query_multi_args()
# all type check null
for col_name, col_type in self.column_dict.items():
fun_name = f"sf_null_{col_name}"
sql = f'select {fun_name}({col_name}) from {self.stbname}'
tdSql.query(sql)
if col_type != "timestamp":
tdSql.checkData(0, 0, "None")
else:
val = tdSql.getData(0, 0)
if val is not None:
tdLog.exit(f" check {sql} not expect None.")
# concat
sql = f'select sf_concat_var(col12, t12), concat(col12, t12) from {self.stbname} limit 1000'
self.verify_same_value(sql)
sql = f'select sf_concat_nch(col13, t13), concat(col13, t13) from {self.stbname} limit 1000'
self.verify_same_value(sql)
# create aggregate
def create_aggr_udfpy(self):
bufsize = 200 * 1024
# all type check null
for col_name, col_type in self.column_dict.items():
self.create_udf_af(f"af_null_{col_name}", "af_null.py", col_type, bufsize)
# min
file_name = "af_min.py"
fun_name = "af_min_float"
self.create_udf_af(fun_name, file_name, f"float", bufsize)
fun_name = "af_min_int"
self.create_udf_af(fun_name, file_name, f"int", bufsize)
# sum
file_name = "af_sum.py"
fun_name = "af_sum_float"
self.create_udf_af(fun_name, file_name, f"float", bufsize)
fun_name = "af_sum_int"
self.create_udf_af(fun_name, file_name, f"int", bufsize)
fun_name = "af_sum_bigint"
self.create_udf_af(fun_name, file_name, f"bigint", bufsize)
# count
file_name = "af_count.py"
fun_name = "af_count_float"
self.create_udf_af(fun_name, file_name, f"float", bufsize)
fun_name = "af_count_int"
self.create_udf_af(fun_name, file_name, f"int", bufsize)
fun_name = "af_count_bigint"
self.create_udf_af(fun_name, file_name, f"bigint", bufsize)
# query aggregate
def query_aggr_udfpy(self) :
# all type check null
for col_name, col_type in self.column_dict.items():
fun_name = f"af_null_{col_name}"
sql = f'select {fun_name}({col_name}) from {self.stbname}'
tdSql.query(sql)
if col_type != "timestamp":
tdSql.checkData(0, 0, "None")
else:
val = tdSql.getData(0, 0)
if val is not None:
tdLog.exit(f" check {sql} not expect None.")
# min
sql = f'select min(col3), af_min_int(col3) from {self.stbname}'
self.verify_same_value(sql)
sql = f'select min(col7), af_min_int(col7) from {self.stbname}'
self.verify_same_value(sql)
sql = f'select min(col9), af_min_float(col9) from {self.stbname}'
self.verify_same_value(sql)
# sum
sql = f'select sum(col1), af_sum_int(col1) from d0'
self.verify_same_value(sql)
sql = f'select sum(col3), af_sum_bigint(col3) from {self.stbname}'
self.verify_same_value(sql)
sql = f'select sum(col9), af_sum_float(col9) from {self.stbname}'
self.verify_same_value(sql)
# count
sql = f'select count(col1), af_count_int(col1) from {self.stbname}'
self.verify_same_value(sql)
sql = f'select count(col7), af_count_bigint(col7) from {self.stbname}'
self.verify_same_value(sql)
sql = f'select count(col8), af_count_float(col8) from {self.stbname}'
self.verify_same_value(sql)
# nest
sql = f'select a+1000,b+1000 from (select count(col8) as a, af_count_float(col8) as b from {self.stbname})'
self.verify_same_value(sql)
# group by
sql = f'select a+1000,b+1000 from (select count(col8) as a, af_count_float(col8) as b from {self.stbname} group by tbname)'
self.verify_same_value(sql)
# two filed expr
sql = f'select sum(col1+col2),af_sum_float(col1+col2) from {self.stbname};'
self.verify_same_value(sql)
# interval
sql = f'select af_sum_float(col2+col3),sum(col3+col2) from {self.stbname} interval(1s)'
self.verify_same_value(sql)
# insert to child table d1 data
def insert_data(self, tbname, rows):
ts = 1670000000000
values = ""
batch_size = 500
child_name = ""
for i in range(self.child_count):
for j in range(rows):
tj = j % 128
cols = f'{tj},{tj},{j},{j},{tj},{tj},{j},{j},{j}.000{j},{j}.000{j},true,"var{j}","nch{j}涛思数据codepage is utf_32_le"'
value = f'({ts+j},{cols})'
if values == "":
values = value
else:
values += f",{value}"
if j % batch_size == 0 or j + 1 == rows:
sql = f'insert into {tbname}{i} values {values};'
tdSql.execute(sql)
tdLog.info(f" child table={i} rows={j} insert data.")
values = ""
# partial columns upate
sql = f'insert into {tbname}0(ts, col1, col9, col11) values(now, 100, 200, 0)'
tdSql.execute(sql)
sql = f'insert into {tbname}0(ts, col2, col5, col8) values(now, 100, 200, 300)'
tdSql.execute(sql)
sql = f'insert into {tbname}0(ts, col3, col7, col13) values(now, null, null, null)'
tdSql.execute(sql)
sql = f'insert into {tbname}0(ts) values(now)'
tdSql.execute(sql)
tdLog.info(f" insert {rows} to child table {self.child_count} .")
# create stream
def create_stream(self):
sql = f"create stream ma into sta subtable(concat('sta_',tbname)) \
as select _wstart,count(col1),af_count_bigint(col1) from {self.stbname} partition by tbname interval(1s);"
tdSql.execute(sql)
tdLog.info(sql)
# query stream
def verify_stream(self):
sql = f"select * from sta limit 10"
self.verify_same_value(sql, 1)
# create tmq
def create_tmq(self):
sql = f"create topic topa as select concat(col12,t12),sf_concat_var(col12,t12) from {self.stbname};"
tdSql.execute(sql)
tdLog.info(sql)
def install_taospy(self):
tdLog.info("install taospyudf...")
packs = ["taospyudf"]
for pack in packs:
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '-i', 'https://pypi.org/simple', '-U', pack])
tdLog.info("call ldconfig...")
os.system("ldconfig")
tdLog.info("install taospyudf successfully.")
# run
def run(self):
self.install_taospy()
# var
stable = "meters"
tbname = "d"
count = 10
rows = 5000
# do
self.create_table(stable, tbname, count)
# create
self.create_scalar_udfpy()
self.create_aggr_udfpy()
# create stream
self.create_stream()
# create tmq
self.create_tmq()
# insert data
self.insert_data(tbname, rows)
# query
self.query_scalar_udfpy()
self.query_aggr_udfpy()
# show performance
def stop(self):
tdSql.close()
tdLog.success("%s successfully executed" % __file__)
tdCases.addWindows(__file__, TDTestCase())
tdCases.addLinux(__file__, TDTestCase())
......@@ -146,7 +146,7 @@ class TDTestCase:
for i in range(expectRows):
totalConsumeRows += resultList[i]
tdSql.query(queryString)
tdSql.query(queryString, None, 50)
totalRowsFromQury = tdSql.getRows()
tdLog.info("act consume rows: %d, act query rows: %d"%(totalConsumeRows, totalRowsFromQury))
......@@ -236,7 +236,7 @@ class TDTestCase:
for i in range(expectRows):
totalConsumeRows += resultList[i]
tdSql.query(queryString)
tdSql.query(queryString, None, 50)
totalRowsFromQuery = tdSql.getRows()
tdLog.info("act consume rows: %d, expect consume rows: %d"%(totalConsumeRows, totalRowsFromQuery))
......
......@@ -84,15 +84,15 @@ SWords shellCommands[] = {
{"create table <anyword> using <stb_name> tags(", 0, 0, NULL},
{"create database <anyword> <db_options> <anyword> <db_options> <anyword> <db_options> <anyword> <db_options> "
"<anyword> <db_options> <anyword> <db_options> <anyword> <db_options> <anyword> <db_options> <anyword> "
"<db_options> <anyword> <db_options> <anyword> ;",
0, 0, NULL},
"<db_options> <anyword> <db_options> <anyword> ;", 0, 0, NULL},
{"create dnode <anyword>", 0, 0, NULL},
{"create index <anyword> on <stb_name> ()", 0, 0, NULL},
{"create mnode on dnode <dnode_id> ;", 0, 0, NULL},
{"create qnode on dnode <dnode_id> ;", 0, 0, NULL},
{"create stream <anyword> into <anyword> as select", 0, 0, NULL}, // 26 append sub sql
{"create topic <anyword> as select", 0, 0, NULL}, // 27 append sub sql
{"create function ", 0, 0, NULL},
{"create function <anyword> as <anyword> outputtype <data_types> language <udf_language>", 0, 0, NULL},
{"create aggregate function <anyword> as <anyword> outputtype <data_types> bufsize <anyword> language <udf_language>", 0, 0, NULL},
{"create user <anyword> pass <anyword> sysinfo 0;", 0, 0, NULL},
{"create user <anyword> pass <anyword> sysinfo 1;", 0, 0, NULL},
{"describe <all_table>", 0, 0, NULL},
......@@ -105,7 +105,7 @@ SWords shellCommands[] = {
{"drop qnode on dnode <dnode_id> ;", 0, 0, NULL},
{"drop user <user_name> ;", 0, 0, NULL},
// 40
{"drop function", 0, 0, NULL},
{"drop function <udf_name> ;", 0, 0, NULL},
{"drop consumer group <anyword> on ", 0, 0, NULL},
{"drop topic <topic_name> ;", 0, 0, NULL},
{"drop stream <stream_name> ;", 0, 0, NULL},
......@@ -272,6 +272,8 @@ char* key_systable[] = {
"ins_subscriptions", "ins_streams", "ins_stream_tasks", "ins_vnodes", "ins_user_privileges", "perf_connections",
"perf_queries", "perf_consumers", "perf_trans", "perf_apps"};
char* udf_language[] = {"\'Python\'", "\'C\'"};
//
// ------- global variant define ---------
//
......@@ -291,25 +293,29 @@ bool waitAutoFill = false;
#define WT_VAR_USERNAME 4
#define WT_VAR_TOPIC 5
#define WT_VAR_STREAM 6
#define WT_VAR_ALLTABLE 7
#define WT_VAR_FUNC 8
#define WT_VAR_KEYWORD 9
#define WT_VAR_TBACTION 10
#define WT_VAR_DBOPTION 11
#define WT_VAR_ALTER_DBOPTION 12
#define WT_VAR_DATATYPE 13
#define WT_VAR_KEYTAGS 14
#define WT_VAR_ANYWORD 15
#define WT_VAR_TBOPTION 16
#define WT_VAR_USERACTION 17
#define WT_VAR_KEYSELECT 18
#define WT_VAR_SYSTABLE 19
#define WT_VAR_CNT 20
#define WT_FROM_DB_MAX 6 // max get content from db
#define WT_VAR_UDFNAME 7
#define WT_FROM_DB_MAX 7 // max get content from db
#define WT_FROM_DB_CNT (WT_FROM_DB_MAX + 1)
#define WT_VAR_ALLTABLE 8
#define WT_VAR_FUNC 9
#define WT_VAR_KEYWORD 10
#define WT_VAR_TBACTION 11
#define WT_VAR_DBOPTION 12
#define WT_VAR_ALTER_DBOPTION 13
#define WT_VAR_DATATYPE 14
#define WT_VAR_KEYTAGS 15
#define WT_VAR_ANYWORD 16
#define WT_VAR_TBOPTION 17
#define WT_VAR_USERACTION 18
#define WT_VAR_KEYSELECT 19
#define WT_VAR_SYSTABLE 20
#define WT_VAR_LANGUAGE 21
#define WT_VAR_CNT 22
#define WT_TEXT 0xFF
char dbName[256] = ""; // save use database name;
......@@ -319,13 +325,13 @@ TdThreadMutex tiresMutex;
// save thread handle obtain var name from db server
TdThread* threads[WT_FROM_DB_CNT];
// obtain var name with sql from server
char varTypes[WT_VAR_CNT][64] = {"<db_name>", "<stb_name>", "<tb_name>", "<dnode_id>", "<user_name>",
"<topic_name>", "<stream_name>", "<all_table>", "<function>", "<keyword>",
"<tb_actions>", "<db_options>", "<alter_db_options>", "<data_types>", "<key_tags>",
"<anyword>", "<tb_options>", "<user_actions>", "<key_select>"};
char varTypes[WT_VAR_CNT][64] = {
"<db_name>", "<stb_name>", "<tb_name>", "<dnode_id >", "<user_name>", "<topic_name>", "<stream_name>",
"<udf_name>", "<all_table>", "<function>", "<keyword>", "<tb_actions>", "<db_options>", "<alter_db_options>",
"<data_types>", "<key_tags>", "<anyword>", "<tb_options>", "<user_actions>", "<key_select>", "<sys_table>", "<udf_language>"};
char varSqls[WT_FROM_DB_CNT][64] = {"show databases;", "show stables;", "show tables;", "show dnodes;",
"show users;", "show topics;", "show streams;"};
"show users;", "show topics;", "show streams;", "show functions;"};
// var words current cursor, if user press any one key except tab, cursorVar can be reset to -1
int cursorVar = -1;
......@@ -390,7 +396,8 @@ void showHelp() {
create qnode on dnode <dnode_id> ;\n\
create stream <stream_name> into <stb_name> as select ...\n\
create topic <topic_name> as select ...\n\
create function ...\n\
create function <udf_name> as <file_name> outputtype <data_types> language \'C\' | \'Python\' ;\n\
create aggregate function <udf_name> as <file_name> outputtype <data_types> bufsize <bufsize_bytes> language \'C\' | \'Python\';\n\
create user <user_name> pass <password> ...\n\
----- D ----- \n\
describe <all_table>\n\
......@@ -401,7 +408,7 @@ void showHelp() {
drop mnode on dnode <dnode_id> ;\n\
drop qnode on dnode <dnode_id> ;\n\
drop user <user_name> ;\n\
drop function <function_name>;\n\
drop function <udf_name>;\n\
drop consumer group ... \n\
drop topic <topic_name> ;\n\
drop stream <stream_name> ;\n\
......@@ -643,6 +650,7 @@ bool shellAutoInit() {
GenerateVarType(WT_VAR_USERACTION, user_actions, sizeof(user_actions) / sizeof(char*));
GenerateVarType(WT_VAR_KEYSELECT, key_select, sizeof(key_select) / sizeof(char*));
GenerateVarType(WT_VAR_SYSTABLE, key_systable, sizeof(key_systable) / sizeof(char*));
GenerateVarType(WT_VAR_LANGUAGE, udf_language, sizeof(udf_language) / sizeof(char*));
return true;
}
......
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