mirror of
https://github.com/ceph/s3-tests.git
synced 2024-11-22 09:29:43 +00:00
381 lines
15 KiB
Python
381 lines
15 KiB
Python
import boto3
|
|
import botocore.session
|
|
from botocore.exceptions import ClientError
|
|
from botocore.exceptions import ParamValidationError
|
|
from nose.tools import eq_ as eq
|
|
from nose.plugins.attrib import attr
|
|
from nose.plugins.skip import SkipTest
|
|
import isodate
|
|
import email.utils
|
|
import datetime
|
|
import threading
|
|
import re
|
|
import pytz
|
|
from collections import OrderedDict
|
|
import requests
|
|
import json
|
|
import base64
|
|
import hmac
|
|
import hashlib
|
|
import xml.etree.ElementTree as ET
|
|
import time
|
|
import operator
|
|
import nose
|
|
import os
|
|
import string
|
|
import random
|
|
import socket
|
|
import ssl
|
|
from email.header import decode_header
|
|
|
|
from .utils import assert_raises
|
|
from .utils import generate_random
|
|
from .utils import _get_status_and_error_code
|
|
from .utils import _get_status
|
|
|
|
from .policy import Policy, Statement, make_json_policy
|
|
|
|
from . import (
|
|
get_client,
|
|
get_prefix,
|
|
get_unauthenticated_client,
|
|
get_bad_auth_client,
|
|
get_v2_client,
|
|
get_new_bucket,
|
|
get_new_bucket_name,
|
|
get_new_bucket_resource,
|
|
get_config_is_secure,
|
|
get_config_host,
|
|
get_config_port,
|
|
get_config_endpoint,
|
|
get_main_aws_access_key,
|
|
get_main_aws_secret_key,
|
|
get_main_display_name,
|
|
get_main_user_id,
|
|
get_main_email,
|
|
get_main_api_name,
|
|
get_alt_aws_access_key,
|
|
get_alt_aws_secret_key,
|
|
get_alt_display_name,
|
|
get_alt_user_id,
|
|
get_alt_email,
|
|
get_alt_client,
|
|
get_tenant_client,
|
|
get_tenant_iam_client,
|
|
get_tenant_user_id,
|
|
get_buckets_list,
|
|
get_objects_list,
|
|
get_main_kms_keyid,
|
|
get_secondary_kms_keyid,
|
|
nuke_prefixed_buckets,
|
|
)
|
|
|
|
import boto
|
|
import boto.s3.connection
|
|
import sys
|
|
import random
|
|
from botocore.client import Config
|
|
|
|
endpoint = 'http://localhost:8000'
|
|
access_key = 'b2345678901234567890'
|
|
secret_key = 'b234567890123456789012345678901234567890'
|
|
region_name = ''
|
|
|
|
def get_connection():
|
|
conn = boto.connect_s3(
|
|
aws_access_key_id = access_key,
|
|
aws_secret_access_key = secret_key,
|
|
host = 'localhost', port = 8000 ,
|
|
is_secure=False, # uncomment if you are not using ssl
|
|
calling_format = boto.s3.connection.OrdinaryCallingFormat(),
|
|
)
|
|
|
|
return conn
|
|
|
|
def create_csv_object_for_datetime(rows,columns):
|
|
result = ""
|
|
for i in range(rows):
|
|
row = "";
|
|
for y in range(columns):
|
|
row = row + "{}{:02d}{:02d}-{:02d}{:02d}{:02d},".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"):
|
|
result = ""
|
|
for i in range(rows):
|
|
row = "";
|
|
for y in range(columns):
|
|
row = row + "{}{}".format(random.randint(0,1000),col_delim);
|
|
result += row + record_delim
|
|
|
|
return result
|
|
|
|
|
|
def upload_csv_object(bucket_name,new_key,obj):
|
|
conn = get_connection()
|
|
conn.create_bucket( bucket_name )
|
|
bucket = conn.get_bucket( bucket_name )
|
|
|
|
k1 = bucket.new_key( new_key );
|
|
k1.set_contents_from_string( obj );
|
|
|
|
|
|
def run_s3select(bucket,key,query,column_delim=",",row_delim="\n",quot_char='"',esc_char='\\'):
|
|
s3 = boto3.client('s3',#'sns',
|
|
endpoint_url=endpoint,
|
|
aws_access_key_id=access_key,
|
|
region_name=region_name,
|
|
aws_secret_access_key=secret_key)
|
|
#config=Config(signature_version='v2'))
|
|
|
|
|
|
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}, "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):
|
|
res = 0
|
|
list_of_int = []
|
|
for rec in obj.split("\n"):
|
|
col_num = 1
|
|
if ( len(rec) == 0):
|
|
continue;
|
|
for col in rec.split(","):
|
|
if (col_num == column_pos):
|
|
list_of_int.append(int(col));
|
|
col_num+=1;
|
|
|
|
return list_of_int
|
|
|
|
def test_count_operation():
|
|
csv_obj_name = "csv_star_oper"
|
|
bucket_name = "test"
|
|
num_of_rows = 10
|
|
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(",","")
|
|
|
|
assert num_of_rows == int( res )
|
|
|
|
def test_column_sum_min_max():
|
|
csv_obj = create_random_csv_object(10000,10)
|
|
|
|
csv_obj_name = "csv_10000x10"
|
|
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)) from stdin;") ).replace(",","")
|
|
list_int = create_list_of_int( 1 , csv_obj )
|
|
res_target = min( list_int )
|
|
|
|
assert 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 )
|
|
|
|
assert int(res_s3select) == int(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 )
|
|
|
|
assert 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 )
|
|
|
|
assert 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 )
|
|
|
|
assert 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 )
|
|
|
|
assert int(res_s3select) == int(res_target)
|
|
|
|
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"
|
|
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","")
|
|
|
|
# assert is according to radom-csv function
|
|
assert res_s3select == "0,1000,1,"
|
|
|
|
# purpose of test that all where conditions create the same group of values, thus same result
|
|
res_s3select_substr = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select min(int(_2)),max(int(_2)) from stdin where substr(_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","")
|
|
|
|
assert res_s3select_substr == res_s3select_between_numbers
|
|
|
|
assert res_s3select_between_numbers == res_s3select_eq_modolu
|
|
|
|
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 = "csv_10000x10"
|
|
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(",","")
|
|
|
|
assert res_s3select_alias == res_s3select_no_alias
|
|
|
|
|
|
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(10000,10)
|
|
|
|
csv_obj_name = "csv_10000x10"
|
|
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
|
|
|
|
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 = "csv_datetime_10000x10"
|
|
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",timestamp(_1)) > 1950 and extract("year",timestamp(_1)) < 1960;') )
|
|
|
|
res_s3select_substr = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where int(substr(_1,1,4))>1950 and int(substr(_1,1,4))<1960;') )
|
|
|
|
assert res_s3select_date_time == res_s3select_substr
|
|
|
|
res_s3select_date_time = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin where datediff("month",timestamp(_1),dateadd("month",2,timestamp(_1)) ) == 2;') )
|
|
|
|
res_s3select_count = remove_xml_tags_from_result( run_s3select(bucket_name,csv_obj_name,'select count(0) from stdin;') )
|
|
|
|
assert 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 datediff("year",timestamp(_1),dateadd("day", 366 ,timestamp(_1))) == 1 ;') )
|
|
|
|
assert 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 datediff("hours",utcnow(),dateadd("day",1,utcnow())) == 24 ;') )
|
|
|
|
assert res_s3select_date_time_utcnow == res_s3select_count
|
|
|
|
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 = "csv_one_line"
|
|
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","")
|
|
assert 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","")
|
|
assert 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","")
|
|
assert 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","")
|
|
assert res_s3select_alias == ','
|
|
|
|
# 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","")
|
|
assert res_s3select_alias == ','
|
|
|
|
# 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","")
|
|
assert res_s3select_alias == ','
|
|
|
|
# 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","")
|
|
assert res_s3select_alias == ','
|
|
|
|
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 = "csv_pipeSign_tab_eol"
|
|
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(",","")
|
|
|
|
assert number_of_rows == int(res)
|
|
|
|
# assert is according to radom-csv function
|
|
# purpose of test is validate that tokens are processed correctly
|
|
res = 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","")
|
|
|
|
assert res == "0,1000,1,"
|
|
|