test: first submit udf python case

tests/system-test/0-others/udfpy/af_min.py

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+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 < 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) 

tests/system-test/0-others/udfpy/af_null.py

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+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) 

tests/system-test/0-others/udfpy/af_sum.py

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+import pickle
+
+def init():
+    pass
+
+def destroy():
+    pass
+
+def start():
+    return pickle.dumps([])
+
+def finish(buf):
+    sums = pickle.loads(buf)
+    all = 0
+    for sum in sums:
+        all += sum
+    return all
+
+def reduce(datablock, buf):
+    (rows, cols) = datablock.shape()
+    sums = pickle.loads(buf)
+    sum = 0
+    for i in range(rows):
+        val = datablock.data(i, 0)
+        if val is not None:
+           sum += val
+    sums.append(sum)
+    return pickle.dumps(sums) 

tests/system-test/0-others/udfpy/sf_multi_args.py

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+# init
+def init():
+    pass
+
+# destory
+def destory():
+    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)
+            rows.append(val)
+        results.append(','.join(rows))
+    return results
+

tests/system-test/0-others/udfpy/sf_null.py

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+
+# init
+def init():
+    pass
+
+# destory
+def destory():
+    pass
+
+# return origin column one value 
+def process(block):
+    (rows, cols) = block.shape()
+    results = []
+    for i in range(rows):
+        results.append(None)
+    return results

tests/system-test/0-others/udfpy/sf_origin.py

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+# init
+def init():
+    pass
+
+# destory
+def destory():
+    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

tests/system-test/0-others/udfpy_main.py

@@ -0,0 +1,298 @@
+###################################################################
+#           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
+
+
+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(20)',
+            'col13': 'nchar(20)',
+            'col14': 'timestamp'
+        }
+        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(20)',
+            't13': 'nchar(20)',
+            't14': 'timestamp'            
+        }
+
+    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.prepare()
+        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)
+
+        # 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}",now'
+            sql  = f'create table {tbname}{i} using {stbname} tags({tags})'
+            tdSql.execute(sql)
+
+        tdLog.info(f" create {count} child tables ok.")
+
+    def create_udfpy_impl(self, funs, filename):
+        for name, outtype in funs.items():
+            sql = f' create function {name} as "{self.udf_path}/{filename} {outtype} " language "Python" '
+            tdSql.execute(sql)
+
+
+    def create_udfpy_dicts(self, dicts, filename):
+        for k,v in dicts:
+            self.create_udfpy_impl(k, v, filename)
+
+    # create_udfpy_function
+    def create_udfpy_function(self):
+        # function
+
+
+        # scalar funciton
+        self.scalar_funs = {
+            '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(20)',
+            'sf13': 'nchar(20)',
+            'sf14': 'timestamp'            
+        }
+        # 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(20)',
+            'af13': 'nchar(20)',
+            'af14': 'timestamp'            
+        }
+
+        # files
+        self.create_udfpy_function(self.scalar_funs, "fun_origin")
+        self.create_udf_sf("sf_multi_args", "binary(1024)")
+
+        #self.create_udfpy_function(self.agg_funs, None)
+
+    def create_udf_sf(self, fun_name, out_type):
+        sql = f'create function {fun_name} as {self.udf_path}{fun_name}.py {out_type} language "Python"'
+        tdSql.execute(sql)
+
+    def create_udf_af(self, fun_name, out_type, bufsize):
+        sql = f'create aggregate function {fun_name} as {self.udf_path}{fun_name}.py {out_type} bufsize {bufsize} language "Python"'
+        tdSql.execute(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 verfiy_same_value(sql):
+        tdSql.query(sql)
+        nrows = tdSql.getRows()
+        for i in range(nrows):
+            val = tdSql.getData(i, 0)
+            tdSql.checkData(i, 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 = self.column_dict.keys() + self.tag_dict.keys()
+        ncols = len(cols)
+        for i in range(2, ncols):
+            sample = random.sample(i)
+            cols_name = ','.join(sample)
+            sql = f'select  sf_multi_args({cols_name}),{cols_name} from {self.stbname}'
+            self.verify_same_multi_values(sql)
+
+    
+    # query_udfpy
+    def query_scalar_udfpy(self):
+        # col
+        for col_name, col_type in self.column_dict:
+           for fun_name, out_type in self.scalar_funs:
+               sql = f'select {col_name} {fun_name}({col_name}) from {self.stbname}'
+               self.verify_same_value(sql)
+
+        # multi-args
+        self.query_multi_args()       
+
+    # create aggregate 
+    def create_aggr_udfpy(self):
+        # all type check null
+        for col_name, col_type in self.column_dict:
+             self.create_udf_af(f"af_null_{col_name}", f"{col_type}", 10*1024*1024)
+
+        # min
+        self.create_udf_af(f"af_min_float", f"float", 10*1024*1024)
+        self.create_udf_af(f"af_min_int", f"int", 10*1024*1024)
+
+        # sum
+        self.create_udf_af(f"af_sum_float", f"float", 100*1024*1024)
+        self.create_udf_af(f"af_sum_int", f"sum", 100*1024*1024)
+
+
+    # query aggregate 
+    def query_aggr_udfpy(self) :
+        # all type check null
+        for col_name, col_type in self.column_dict:
+             fun_name = f"af_null_{col_name}"
+             sql = f'select {fun_name}(col_name) from {self.stbname}'
+             tdSql.query(sql)
+             tdSql.checkData(0, 0, "NULL")
+
+        # min
+        sql = f'select min(col3), af_min_int(col3) from {self.stbname}'
+        self.verfiy_same_value(sql)
+        sql = f'select min(col7), af_min_int(col7) from {self.stbname}'
+        self.verfiy_same_value(sql)
+        sql = f'select min(col9), af_min_float(col9) from {self.stbname}'
+        self.verfiy_same_value(sql)
+
+        # sum
+        sql = f'select sum(col3), af_sum_int(col3) from {self.stbname}'
+        self.verfiy_same_value(sql)
+        sql = f'select sum(col7), af_sum_int(col7) from {self.stbname}'
+        self.verfiy_same_value(sql)
+        sql = f'select sum(col9), af_sum_float(col9) from {self.stbname}'
+        self.verfiy_same_value(sql)
+
+
+            
+    
+    # insert to child table d1 data
+    def insert_data(self, tbname, rows):
+        ts = 1670000000000
+        for i in range(self.child_count):
+            for j in range(rows):
+                ti = j % 128
+                cols = f'{ti},{ti},{i},{i},{ti},{ti},{i},{i},{i}.000{i},{i}.000{i},true,"var{i}","nch{i}",now'
+                sql = f'insert into {tbname}{i} values({ts+j},{cols});' 
+                tdSql.execute(sql)
+
+        tdLog.info(f" insert {rows} for each child table.")
+
+
+    # run
+    def run(self):
+        # var
+        stable = "meters"
+        tbname = "d"
+        count = 100
+        # do 
+        self.create_table(stable, tbname, count)
+        self.insert_data(tbname, 1000)
+
+        # scalar
+        self.create_scalar_udfpy()
+        self.query_scalar_udfpy()
+
+        # aggregate
+        self.create_aggr_udfpy()
+        self.query_aggr_udfpy()
+
+
+
+
+    def stop(self):
+        tdSql.close()
+        tdLog.success("%s successfully executed" % __file__)
+
+tdCases.addWindows(__file__, TDTestCase())
+tdCases.addLinux(__file__, TDTestCase())