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per each new uploaded file(for test), it got unique name(random), and uploaded file is verified for its content

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Signed-off-by: gal salomon <gal.salomon@gmail.com>

Signed-off-by: gal salomon <gal.salomon@gmail.com>
This commit is contained in:
gal salomon 2020-07-03 14:49:13 +03:00
parent 982d15c30e
commit 350fcbb4ec
1 changed files with 46 additions and 15 deletions
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61
s3tests_boto3/functional/test_s3select.py
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@ -2,6 +2,8 @@ import nose
import random
from nose.plugins.attrib import attr
import uuid
from nose.tools import eq_ as eq
from . import (
get_client
@ -63,12 +65,16 @@ def generate_s3select_expression_projection(bucket_name,obj_name):
assert (1 - (float(res.split("\n")[1]) / eval( e )) ) < epsilon
@attr('s3select')
def get_random_string():
return uuid.uuid4().hex[:6].upper()
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 = "single_line_csv.csv"
obj_name = get_random_string() #"single_line_csv.csv"
upload_csv_object(bucket_name,obj_name,single_line_csv)
for _ in range(100):
@ -80,7 +86,7 @@ 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 = "single_line_csv.csv"
obj_name = get_random_string() #"single_line_csv.csv"
upload_csv_object(bucket_name,obj_name,single_line_csv)
for _ in range(100):
@ -116,6 +122,12 @@ 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"):
@ -162,9 +174,9 @@ def create_list_of_int(column_pos,obj,field_split=",",row_split="\n"):
@attr('s3select')
def test_count_operation():
csv_obj_name = "csv_star_oper"
csv_obj_name = get_random_string()
bucket_name = "test"
num_of_rows = 10
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(",","")
@ -175,13 +187,13 @@ def test_count_operation():
def test_column_sum_min_max():
csv_obj = create_random_csv_object(10000,10)
csv_obj_name = "csv_10000x10"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
csv_obj_name = "csv_10000x10"
csv_obj_name_2 = get_random_string()
bucket_name_2 = "testbuck2"
upload_csv_object(bucket_name_2,csv_obj_name,csv_obj)
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 )
@ -220,7 +232,7 @@ def test_column_sum_min_max():
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,"select count(0),sum(int(_1)),sum(int(_2)) from stdin where (int(_1)-int(_2)) == 2;" ) )
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 ) )
@ -236,7 +248,7 @@ 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 = "csv_100000x10"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -272,7 +284,7 @@ def test_alias():
csv_obj = create_random_csv_object(10000,10)
csv_obj_name = "csv_10000x10"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -291,7 +303,7 @@ def test_alias_cyclic_refernce():
# 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 = "csv_10000x10"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -309,7 +321,7 @@ def test_datetime():
csv_obj = create_csv_object_for_datetime(10000,1)
csv_obj_name = "csv_datetime_10000x10"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -342,7 +354,7 @@ def test_csv_parser():
# 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 = "csv_one_line"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -383,7 +395,7 @@ def test_csv_definition():
#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 = "csv_pipeSign_tab_eol"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -413,7 +425,7 @@ def test_schema_definition():
# 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 = "csv_with_header_info"
csv_obj_name = get_random_string()
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
@ -436,3 +448,22 @@ def test_schema_definition():
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_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," )