import nose import random import string from nose.plugins.attrib import attr import uuid from nose.tools import eq_ as eq from . import ( get_client ) region_name = '' # recurssion function for generating arithmetical expression def random_expr(depth): # depth is the complexity of expression if depth==1 : return str(int(random.random() * 100) + 1)+".0" return '(' + random_expr(depth-1) + random.choice(['+','-','*','/']) + random_expr(depth-1) + ')' def generate_s3select_where_clause(bucket_name,obj_name): a=random_expr(4) b=random_expr(4) s=random.choice([ '<','>','==','<=','>=','!=' ]) try: eval( a ) eval( b ) except ZeroDivisionError: return # generate s3select statement using generated randome expression # upon count(0)>0 it means true for the where clause expression # the python-engine {eval( conditional expression )} should return same boolean result. s3select_stmt = "select count(0) from stdin where " + a + s + b + ";" res = remove_xml_tags_from_result( run_s3select(bucket_name,obj_name,s3select_stmt) ).replace(",","") nose.tools.assert_equal(int(res)>0 , eval( a + s + b )) def generate_s3select_expression_projection(bucket_name,obj_name): # generate s3select statement using generated randome expression # statement return an arithmetical result for the generated expression. # the same expression is evaluated by python-engine, result should be close enough(Epsilon) e = random_expr( 4 ) try: eval( e ) except ZeroDivisionError: return if eval( e ) == 0: return res = remove_xml_tags_from_result( run_s3select(bucket_name,obj_name,"select " + e + " from stdin;",) ).replace(",","") # accuracy level epsilon = float(0.000001) # both results should be close (epsilon) assert (1 - (float(res.split("\n")[1]) / eval( e )) ) < epsilon @attr('s3select') def get_random_string(): return uuid.uuid4().hex[:6].upper() @attr('s3select') def test_generate_where_clause(): # create small csv file for testing the random expressions single_line_csv = create_random_csv_object(1,1) bucket_name = "test" obj_name = get_random_string() #"single_line_csv.csv" upload_csv_object(bucket_name,obj_name,single_line_csv) for _ in range(100): generate_s3select_where_clause(bucket_name,obj_name) @attr('s3select') def test_generate_projection(): # create small csv file for testing the random expressions single_line_csv = create_random_csv_object(1,1) bucket_name = "test" obj_name = get_random_string() #"single_line_csv.csv" upload_csv_object(bucket_name,obj_name,single_line_csv) for _ in range(100): generate_s3select_expression_projection(bucket_name,obj_name) def create_csv_object_for_datetime(rows,columns): result = "" for _ in range(rows): row = "" for _ in range(columns): row = row + "{}{:02d}{:02d}T{:02d}{:02d}{:02d}Z,".format(random.randint(0,100)+1900,random.randint(1,12),random.randint(1,28),random.randint(0,23),random.randint(0,59),random.randint(0,59),) result += row + "\n" return result def create_random_csv_object(rows,columns,col_delim=",",record_delim="\n",csv_schema=""): result = "" if len(csv_schema)>0 : result = csv_schema + record_delim for _ in range(rows): row = "" for _ in range(columns): row = row + "{}{}".format(random.randint(0,1000),col_delim) result += row + record_delim return result def create_random_csv_object_string(rows,columns,col_delim=",",record_delim="\n",csv_schema=""): result = "" if len(csv_schema)>0 : result = csv_schema + record_delim for _ in range(rows): row = "" for _ in range(columns): if random.randint(0,9) == 5: row = row + "{}{}".format(''.join(random.choice(string.ascii_letters) for m in range(10)) + "aeiou",col_delim) else: row = row + "{}{}".format(''.join("cbcd" + random.choice(string.ascii_letters) for m in range(10)) + "vwxyzzvwxyz" ,col_delim) result += row + record_delim return result def create_random_csv_object_trim(rows,columns,col_delim=",",record_delim="\n",csv_schema=""): result = "" if len(csv_schema)>0 : result = csv_schema + record_delim for _ in range(rows): row = "" for _ in range(columns): row = row + "{}{}".format(''.join(" aeiou ") ,col_delim) result += row + record_delim return result def create_random_csv_object_escape(rows,columns,col_delim=",",record_delim="\n",csv_schema=""): result = "" if len(csv_schema)>0 : result = csv_schema + record_delim for _ in range(rows): row = "" for _ in range(columns): if random.randint(0,9) == 5: row = row + "{}{}".format(''.join("_ar") ,col_delim) else: row = row + "{}{}".format(''.join("aeio_") ,col_delim) result += row + record_delim return result def create_random_csv_object_null(rows,columns,col_delim=",",record_delim="\n",csv_schema=""): result = "" if len(csv_schema)>0 : result = csv_schema + record_delim for _ in range(rows): row = "" for _ in range(columns): row = row + "{}{}".format(''.join("") ,col_delim) result += row + record_delim return result def upload_csv_object(bucket_name,new_key,obj): client = get_client() client.create_bucket(Bucket=bucket_name) client.put_object(Bucket=bucket_name, Key=new_key, Body=obj) # validate uploaded object c2 = get_client() response = c2.get_object(Bucket=bucket_name, Key=new_key) eq(response['Body'].read().decode('utf-8'), obj, 's3select error[ downloaded object not equal to uploaded objecy') def run_s3select(bucket,key,query,column_delim=",",row_delim="\n",quot_char='"',esc_char='\\',csv_header_info="NONE"): s3 = get_client() r = s3.select_object_content( Bucket=bucket, Key=key, ExpressionType='SQL', InputSerialization = {"CSV": {"RecordDelimiter" : row_delim, "FieldDelimiter" : column_delim,"QuoteEscapeCharacter": esc_char, "QuoteCharacter": quot_char, "FileHeaderInfo": csv_header_info}, "CompressionType": "NONE"}, OutputSerialization = {"CSV": {}}, Expression=query,) result = "" for event in r['Payload']: if 'Records' in event: records = event['Records']['Payload'].decode('utf-8') result += records return result def remove_xml_tags_from_result(obj): result = "" for rec in obj.split("\n"): if(rec.find("Payload")>0 or rec.find("Records")>0): continue result += rec + "\n" # remove by split return result def create_list_of_int(column_pos,obj,field_split=",",row_split="\n"): list_of_int = [] for rec in obj.split(row_split): col_num = 1 if ( len(rec) == 0): continue for col in rec.split(field_split): if (col_num == column_pos): list_of_int.append(int(col)) col_num+=1 return list_of_int @attr('s3select') def test_count_operation(): csv_obj_name = get_random_string() bucket_name = "test" num_of_rows = 1234 obj_to_load = create_random_csv_object(num_of_rows,10) upload_csv_object(bucket_name,csv_obj_name,obj_to_load) res = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin;") ).replace(",","") nose.tools.assert_equal( num_of_rows, int( res )) @attr('s3select') def test_column_sum_min_max(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) csv_obj_name_2 = get_random_string() bucket_name_2 = "testbuck2" upload_csv_object(bucket_name_2,csv_obj_name_2,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select min(int(_1)) from stdin;") ).replace(",","") list_int = create_list_of_int( 1 , csv_obj ) res_target = min( list_int ) nose.tools.assert_equal( int(res_s3select), int(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select min(int(_4)) from stdin;") ).replace(",","") list_int = create_list_of_int( 4 , csv_obj ) res_target = min( list_int ) nose.tools.assert_equal( int(res_s3select), int(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select avg(int(_6)) from stdin;") ).replace(",","") list_int = create_list_of_int( 6 , csv_obj ) res_target = float(sum(list_int ))/10000 nose.tools.assert_equal( float(res_s3select), float(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select max(int(_4)) from stdin;") ).replace(",","") list_int = create_list_of_int( 4 , csv_obj ) res_target = max( list_int ) nose.tools.assert_equal( int(res_s3select), int(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select max(int(_7)) from stdin;") ).replace(",","") list_int = create_list_of_int( 7 , csv_obj ) res_target = max( list_int ) nose.tools.assert_equal( int(res_s3select), int(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select sum(int(_4)) from stdin;") ).replace(",","") list_int = create_list_of_int( 4 , csv_obj ) res_target = sum( list_int ) nose.tools.assert_equal( int(res_s3select), int(res_target)) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select sum(int(_7)) from stdin;") ).replace(",","") list_int = create_list_of_int( 7 , csv_obj ) res_target = sum( list_int ) nose.tools.assert_equal( int(res_s3select) , int(res_target) ) # the following queries, validates on *random* input an *accurate* relation between condition result,sum operation and count operation. res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name_2,csv_obj_name_2,"select count(0),sum(int(_1)),sum(int(_2)) from stdin where (int(_1)-int(_2)) == 2;" ) ) count,sum1,sum2,d = res_s3select.split(",") nose.tools.assert_equal( int(count)*2 , int(sum1)-int(sum2 ) ) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0),sum(int(_1)),sum(int(_2)) from stdin where (int(_1)-int(_2)) == 4;" ) ) count,sum1,sum2,d = res_s3select.split(",") nose.tools.assert_equal( int(count)*4 , int(sum1)-int(sum2) ) @attr('s3select') def test_nullif_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where nullif(_1,_2) is null ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 == _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (nullif(_1,_2) is null) from stdin ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (_1 == _2) from stdin ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where not nullif(_1,_2) is null ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (nullif(_1,_2) is not null) from stdin ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (_1 != _2) from stdin ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where nullif(_1,_2) == _1 ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) csv_obj = create_random_csv_object_null(10000,10) upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where nullif(_1,null) is null;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where _1 is null;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (nullif(_1,null) is null) from s3object;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select (_1 is null) from s3object;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) @attr('s3select') def test_nulliftrue_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where (nullif(_1,_2) is null) == true ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 == _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where not (nullif(_1,_2) is null) == true ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) res_s3select_nullif = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where (nullif(_1,_2) == _1 == true) ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_nullif, res_s3select) @attr('s3select') def test_is_not_null_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_null = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where nullif(_1,_2) is not null ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_null, res_s3select) res_s3select_null = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where (nullif(_1,_1) and _1 == _2) is not null ;") ).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(*) from s3object where _1 != _2 ;") ).replace("\n","") nose.tools.assert_equal( res_s3select_null, res_s3select) @attr('s3select') def test_lowerupper_expressions(): csv_obj = create_random_csv_object(1,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select lower("AB12cd$$") from stdin ;') ).replace("\n","") nose.tools.assert_equal( res_s3select, "ab12cd$$,") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select upper("ab12CD$$") from stdin ;') ).replace("\n","") nose.tools.assert_equal( res_s3select, "AB12CD$$,") @attr('s3select') def test_in_expressions(): # purpose of test: engine is process correctly several projections containing aggregation-functions csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) in(1);')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) == 1;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_1) in(1)) from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_1) == 1) from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) in(1,0);')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) == 1 or int(_1) == 0;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_1) in(1,0)) from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_1) == 1 or int(_1) == 0) from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2) in(1,0,2);')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2) == 1 or int(_2) == 0 or int(_2) == 2;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_2) in(1,0,2)) from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_2) == 1 or int(_2) == 0 or int(_2) == 2) from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2)*2 in(int(_3)*2,int(_4)*3,int(_5)*5);')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2)*2 == int(_3)*2 or int(_2)*2 == int(_4)*3 or int(_2)*2 == int(_5)*5;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_2)*2 in(int(_3)*2,int(_4)*3,int(_5)*5)) from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (int(_2)*2 == int(_3)*2 or int(_2)*2 == int(_4)*3 or int(_2)*2 == int(_5)*5) from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where character_length(_1) == 2 and substring(_1,2,1) in ("3");')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where _1 like "_3";')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (character_length(_1) == 2 and substring(_1,2,1) in ("3")) from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_1 like "_3") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) @attr('s3select') def test_true_false_in_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where (int(_1) in(1)) == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) == 1;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where (int(_1) in(1,0)) == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where int(_1) == 1 or int(_1) == 0;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where (int(_2) in(1,0,2)) == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2) == 1 or int(_2) == 0 or int(_2) == 2;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where (int(_2)*2 in(int(_3)*2,int(_4)*3,int(_5)*5)) == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_2) from stdin where int(_2)*2 == int(_3)*2 or int(_2)*2 == int(_4)*3 or int(_2)*2 == int(_5)*5;')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) res_s3select_in = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where (character_length(_1) == 2) == true and (substring(_1,2,1) in ("3")) == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select int(_1) from stdin where _1 like "_3";')).replace("\n","") nose.tools.assert_equal( res_s3select_in, res_s3select ) @attr('s3select') def test_like_expressions(): csv_obj = create_random_csv_object_string(1000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _1 like "%aeio%";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,11,4) == "aeio" ;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_1 like "%aeio%") from stdin ;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_1,11,4) == "aeio") from stdin ;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _1 like "cbcd%";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,1,4) == "cbcd";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_1 like "cbcd%") from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_1,1,4) == "cbcd") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _3 like "%y[y-z]";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_3,char_length(_3),1) between "y" and "z" and substring(_3,char_length(_3)-1,1) == "y";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_3 like "%y[y-z]") from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_3,char_length(_3),1) between "y" and "z" and substring(_3,char_length(_3)-1,1) == "y") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _2 like "%yz";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_2,char_length(_2),1) == "z" and substring(_2,char_length(_2)-1,1) == "y";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_2 like "%yz") from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_2,char_length(_2),1) == "z" and substring(_2,char_length(_2)-1,1) == "y") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _3 like "c%z";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_3,char_length(_3),1) == "z" and substring(_3,1,1) == "c";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_3 like "c%z") from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_3,char_length(_3),1) == "z" and substring(_3,1,1) == "c") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _2 like "%xy_";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_2,char_length(_2)-1,1) == "y" and substring(_2,char_length(_2)-2,1) == "x";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select (_2 like "%xy_") from stdin;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select (substring(_2,char_length(_2)-1,1) == "y" and substring(_2,char_length(_2)-2,1) == "x") from stdin;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) @attr('s3select') def test_truefalselike_expressions(): csv_obj = create_random_csv_object_string(1000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_1 like "%aeio%") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,11,4) == "aeio" ;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_1 like "cbcd%") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,1,4) == "cbcd";')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_3 like "%y[y-z]") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where (substring(_3,char_length(_3),1) between "y" and "z") == true and (substring(_3,char_length(_3)-1,1) == "y") == true;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_2 like "%yz") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where (substring(_2,char_length(_2),1) == "z") == true and (substring(_2,char_length(_2)-1,1) == "y") == true;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_3 like "c%z") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where (substring(_3,char_length(_3),1) == "z") == true and (substring(_3,1,1) == "c") == true;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) res_s3select_like = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where (_2 like "%xy_") == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where (substring(_2,char_length(_2)-1,1) == "y") == true and (substring(_2,char_length(_2)-2,1) == "x") == true;')).replace("\n","") nose.tools.assert_equal( res_s3select_like, res_s3select ) @attr('s3select') def test_complex_expressions(): # purpose of test: engine is process correctly several projections containing aggregation-functions csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select min(int(_1)),max(int(_2)),min(int(_3))+1 from stdin;")).replace("\n","") min_1 = min ( create_list_of_int( 1 , csv_obj ) ) max_2 = max ( create_list_of_int( 2 , csv_obj ) ) min_3 = min ( create_list_of_int( 3 , csv_obj ) ) + 1 __res = "{},{},{},".format(min_1,max_2,min_3) # assert is according to radom-csv function nose.tools.assert_equal( res_s3select, __res ) # purpose of test that all where conditions create the same group of values, thus same result res_s3select_substring = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select min(int(_2)),max(int(_2)) from stdin where substring(_2,1,1) == "1"')).replace("\n","") res_s3select_between_numbers = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select min(int(_2)),max(int(_2)) from stdin where int(_2)>=100 and int(_2)<200')).replace("\n","") res_s3select_eq_modolu = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select min(int(_2)),max(int(_2)) from stdin where int(_2)/100 == 1 or int(_2)/10 == 1 or int(_2) == 1')).replace("\n","") nose.tools.assert_equal( res_s3select_substring, res_s3select_between_numbers) nose.tools.assert_equal( res_s3select_between_numbers, res_s3select_eq_modolu) @attr('s3select') def test_alias(): # purpose: test is comparing result of exactly the same queries , one with alias the other without. # this test is setting alias on 3 projections, the third projection is using other projection alias, also the where clause is using aliases # the test validate that where-clause and projections are executing aliases correctly, bare in mind that each alias has its own cache, # and that cache need to be invalidate per new row. csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select int(_1) as a1, int(_2) as a2 , (a1+a2) as a3 from stdin where a3>100 and a3<300;") ).replace(",","") res_s3select_no_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select int(_1),int(_2),int(_1)+int(_2) from stdin where (int(_1)+int(_2))>100 and (int(_1)+int(_2))<300;") ).replace(",","") nose.tools.assert_equal( res_s3select_alias, res_s3select_no_alias) @attr('s3select') def test_alias_cyclic_refernce(): number_of_rows = 10000 # purpose of test is to validate the s3select-engine is able to detect a cyclic reference to alias. csv_obj = create_random_csv_object(number_of_rows,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select int(_1) as a1,int(_2) as a2, a1+a4 as a3, a5+a1 as a4, int(_3)+a3 as a5 from stdin;") ) find_res = res_s3select_alias.find("number of calls exceed maximum size, probably a cyclic reference to alias") assert int(find_res) >= 0 @attr('s3select') def test_datetime(): # purpose of test is to validate date-time functionality is correct, # by creating same groups with different functions (nested-calls) ,which later produce the same result csv_obj = create_csv_object_for_datetime(10000,1) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where extract(year from to_timestamp(_1)) > 1950 and extract(year from to_timestamp(_1)) < 1960;') ) res_s3select_substring = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where int(substring(_1,1,4))>1950 and int(substring(_1,1,4))<1960;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_substring) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where date_diff(month,to_timestamp(_1),date_add(month,2,to_timestamp(_1)) ) == 2;') ) res_s3select_count = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_count) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where date_diff(year,to_timestamp(_1),date_add(day, 366 ,to_timestamp(_1))) == 1 ;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_count) # validate that utcnow is integrate correctly with other date-time functions res_s3select_date_time_utcnow = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where date_diff(hour,utcnow(),date_add(day,1,utcnow())) == 24 ;') ) nose.tools.assert_equal( res_s3select_date_time_utcnow, res_s3select_count) @attr('s3select') def test_true_false_datetime(): # purpose of test is to validate date-time functionality is correct, # by creating same groups with different functions (nested-calls) ,which later produce the same result csv_obj = create_csv_object_for_datetime(10000,1) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where (extract(year from to_timestamp(_1)) > 1950) == true and (extract(year from to_timestamp(_1)) < 1960) == true;') ) res_s3select_substring = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where int(substring(_1,1,4))>1950 and int(substring(_1,1,4))<1960;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_substring) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where (date_diff(month,to_timestamp(_1),date_add(month,2,to_timestamp(_1)) ) == 2) == true;') ) res_s3select_count = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_count) res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where (date_diff(year,to_timestamp(_1),date_add(day, 366 ,to_timestamp(_1))) == 1) == true ;') ) nose.tools.assert_equal( res_s3select_date_time, res_s3select_count) res_s3select_date_time_utcnow = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where (date_diff(hour,utcnow(),date_add(day,1,utcnow())) == 24) == true ;') ) nose.tools.assert_equal( res_s3select_date_time_utcnow, res_s3select_count) @attr('s3select') def test_csv_parser(): # purpuse: test default csv values(, \n " \ ), return value may contain meta-char # NOTE: should note that default meta-char for s3select are also for python, thus for one example double \ is mandatory csv_obj = ',first,,,second,third="c31,c32,c33",forth="1,2,3,4",fifth="my_string=\\"any_value\\" , my_other_string=\\"aaaa,bbb\\" ",' + "\n" csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) # return value contain comma{,} res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _6 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'third="c31,c32,c33",') # return value contain comma{,} res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _7 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'forth="1,2,3,4",') # return value contain comma{,}{"}, escape-rule{\} by-pass quote{"} , the escape{\} is removed. res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _8 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'fifth="my_string="any_value" , my_other_string="aaaa,bbb" ",') # return NULL as first token res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _1 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'null,') # return NULL in the middle of line res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _3 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'null,') # return NULL in the middle of line (successive) res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _4 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'null,') # return NULL at the end line res_s3select_alias = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _9 from stdin;") ).replace("\n","") nose.tools.assert_equal( res_s3select_alias, 'null,') @attr('s3select') def test_csv_definition(): number_of_rows = 10000 #create object with pipe-sign as field separator and tab as row delimiter. csv_obj = create_random_csv_object(number_of_rows,10,"|","\t") csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) # purpose of tests is to parse correctly input with different csv defintions res = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select count(0) from stdin;","|","\t") ).replace(",","") nose.tools.assert_equal( number_of_rows, int(res)) # assert is according to radom-csv function # purpose of test is validate that tokens are processed correctly res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select min(int(_1)),max(int(_2)),min(int(_3))+1 from stdin;","|","\t") ).replace("\n","") min_1 = min ( create_list_of_int( 1 , csv_obj , "|","\t") ) max_2 = max ( create_list_of_int( 2 , csv_obj , "|","\t") ) min_3 = min ( create_list_of_int( 3 , csv_obj , "|","\t") ) + 1 __res = "{},{},{},".format(min_1,max_2,min_3) nose.tools.assert_equal( res_s3select, __res ) @attr('s3select') def test_schema_definition(): number_of_rows = 10000 # purpose of test is to validate functionality using csv header info csv_obj = create_random_csv_object(number_of_rows,10,csv_schema="c1,c2,c3,c4,c5,c6,c7,c8,c9,c10") csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) # ignoring the schema on first line and retrieve using generic column number res_ignore = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select _1,_3 from stdin;",csv_header_info="IGNORE") ).replace("\n","") # using the scheme on first line, query is using the attach schema res_use = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select c1,c3 from stdin;",csv_header_info="USE") ).replace("\n","") # result of both queries should be the same nose.tools.assert_equal( res_ignore, res_use) # using column-name not exist in schema res_multiple_defintion = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select c1,c10,int(c11) from stdin;",csv_header_info="USE") ).replace("\n","") assert res_multiple_defintion.find("alias {c11} or column not exist in schema") > 0 # alias-name is identical to column-name res_multiple_defintion = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select int(c1)+int(c2) as c4,c4 from stdin;",csv_header_info="USE") ).replace("\n","") assert res_multiple_defintion.find("multiple definition of column {c4} as schema-column and alias") > 0 @attr('s3select') def test_when_then_else_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select case when cast(_1 as int)>100 and cast(_1 as int)<200 then "(100-200)" when cast(_1 as int)>200 and cast(_1 as int)<300 then "(200-300)" else "NONE" end from s3object;') ).replace("\n","") count1 = res_s3select.count("(100-200)") count2 = res_s3select.count("(200-300)") count3 = res_s3select.count("NONE") res = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_1 as int)>100 and cast(_1 as int)<200 ;') ).replace("\n","") res1 = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_1 as int)>200 and cast(_1 as int)<300 ;') ).replace("\n","") res2 = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_1 as int)<=100 or cast(_1 as int)>=300 or cast(_1 as int)==200 ;') ).replace("\n","") nose.tools.assert_equal( str(count1) + ',', res) nose.tools.assert_equal( str(count2) + ',', res1) nose.tools.assert_equal( str(count3) + ',', res2) @attr('s3select') def test_coalesce_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where char_length(_3)>2 and char_length(_4)>2 and cast(substring(_3,1,2) as int) == cast(substring(_4,1,2) as int);') ).replace("\n","") res_null = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_3 as int)>99 and cast(_4 as int)>99 and coalesce(nullif(cast(substring(_3,1,2) as int),cast(substring(_4,1,2) as int)),7) == 7;' ) ).replace("\n","") nose.tools.assert_equal( res_s3select, res_null) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select coalesce(nullif(_5,_5),nullif(_1,_1),_2) from stdin;') ).replace("\n","") res_coalesce = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select coalesce(_2) from stdin;') ).replace("\n","") nose.tools.assert_equal( res_s3select, res_coalesce) @attr('s3select') def test_cast_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_3 as int)>999;') ).replace("\n","") res = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where char_length(_3)>3;') ).replace("\n","") nose.tools.assert_equal( res_s3select, res) res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(_3 as int)>99 and cast(_3 as int)<1000;') ).replace("\n","") res = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where char_length(_3)==3;') ).replace("\n","") nose.tools.assert_equal( res_s3select, res) @attr('s3select') def test_version(): return number_of_rows = 1 # purpose of test is to validate functionality using csv header info csv_obj = create_random_csv_object(number_of_rows,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_version = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,"select version() from stdin;") ).replace("\n","") nose.tools.assert_equal( res_version, "41.a," ) @attr('s3select') def test_trim_expressions(): csv_obj = create_random_csv_object_trim(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(_1) == "aeiou";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1 from 4 for 5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(both from _1) == "aeiou";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(trailing from _1) == " aeiou";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(leading from _1) == "aeiou ";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(trim(leading from _1)) == "aeiou";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) @attr('s3select') def test_truefalse_trim_expressions(): csv_obj = create_random_csv_object_trim(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(_1) == "aeiou" == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1 from 4 for 5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(both from _1) == "aeiou" == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(trailing from _1) == " aeiou" == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(leading from _1) == "aeiou " == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) res_s3select_trim = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where trim(trim(leading from _1)) == "aeiou" == true;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,4,5) == "aeiou";')).replace("\n","") nose.tools.assert_equal( res_s3select_trim, res_s3select ) @attr('s3select') def test_escape_expressions(): csv_obj = create_random_csv_object_escape(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_escape = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _1 like "%_ar" escape "%";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,char_length(_1),1) == "r" and substring(_1,char_length(_1)-1,1) == "a" and substring(_1,char_length(_1)-2,1) == "_";')).replace("\n","") nose.tools.assert_equal( res_s3select_escape, res_s3select ) res_s3select_escape = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from stdin where _1 like "%aeio$_" escape "$";')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from stdin where substring(_1,1,5) == "aeio_";')).replace("\n","") nose.tools.assert_equal( res_s3select_escape, res_s3select ) @attr('s3select') def test_case_value_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_case = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select case cast(_1 as int) when cast(_2 as int) then "case_1_1" else "case_2_2" end from s3object;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select case when cast(_1 as int) == cast(_2 as int) then "case_1_1" else "case_2_2" end from s3object;')).replace("\n","") nose.tools.assert_equal( res_s3select_case, res_s3select ) @attr('s3select') def test_bool_cast_expressions(): csv_obj = create_random_csv_object(10000,10) csv_obj_name = get_random_string() bucket_name = "test" upload_csv_object(bucket_name,csv_obj_name,csv_obj) res_s3select_cast = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(*) from s3object where cast(int(_1) as bool) == true ;')).replace("\n","") res_s3select = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name, 'select count(*) from s3object where cast(_1 as int) != 0 ;')).replace("\n","") nose.tools.assert_equal( res_s3select_cast, res_s3select )