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adding radom-generated tests, one for where clause , the second for prjection. random arithmetical expression is generated and used for building s3-select query; result is compared to python-engine
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@ -78,6 +78,90 @@ from botocore.client import Config
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region_name = ''
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# recurssion function for generating arithmetical expression
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def random_expr(depth):
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# depth is the complexity of expression
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if depth==1 :
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return str(int(random.random() * 100) + 1)+".0"
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return '(' + random_expr(depth-1) + random.choice(['+','-','*','/']) + random_expr(depth-1) + ')'
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def generate_s3select_where_clause(bucket_name,obj_name):
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a=random_expr(4)
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b=random_expr(4)
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s=random.choice([ '<','>','==','<=','>=','!=' ])
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try:
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eval( a )
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eval( b )
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except ZeroDivisionError:
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return
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# generate s3select statement using generated randome expression
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# upon count(0)>0 it means true for the where clause expression
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# the python-engine {eval( conditional expression )} should return same boolean result.
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s3select_stmt = "select count(0) from stdin where " + a + s + b + ";"
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res = remove_xml_tags_from_result( run_s3select(bucket_name,obj_name,s3select_stmt) ).replace(",","")
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nose.tools.assert_equal(int(res)>0 , eval( a + s + b ))
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def generate_s3select_expression_projection(bucket_name,obj_name):
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# generate s3select statement using generated randome expression
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# statement return an arithmetical result for the generated expression.
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# the same expression is evaluated by python-engine, result should be close enough(Epsilon)
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e = random_expr( 4 )
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try:
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eval( e )
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except ZeroDivisionError:
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return
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if eval( e ) == 0:
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return
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res = remove_xml_tags_from_result( run_s3select(bucket_name,obj_name,"select " + e + " from stdin;",) ).replace(",","")
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# accuracy level
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epsilon = float(0.1)
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#debug purpose
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x = (1 - (float(res.split("\n")[1]) / eval( e )) )
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if (x > epsilon):
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print (x)
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print (e)
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# both results should be close (epsilon)
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assert (1 - (float(res.split("\n")[1]) / eval( e )) ) < epsilon
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def test_generate_where_clause():
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# create small csv file for testing the random expressions
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single_line_csv = create_random_csv_object(1,1)
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bucket_name = "test"
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obj_name = "single_line_csv.csv"
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upload_csv_object(bucket_name,obj_name,single_line_csv)
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for _ in range(10):
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generate_s3select_where_clause(bucket_name,obj_name)
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def test_generate_projection():
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# skipping until fix for s3select engine accuracy
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return
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# create small csv file for testing the random expressions
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single_line_csv = create_random_csv_object(1,1)
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bucket_name = "test"
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obj_name = "single_line_csv.csv"
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upload_csv_object(bucket_name,obj_name,single_line_csv)
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for _ in range(100):
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generate_s3select_expression_projection(bucket_name,obj_name)
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def get_connection():
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conn = boto.connect_s3(
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aws_access_key_id = get_main_aws_access_key(),
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