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): result = "" for i in range(rows): row = ""; for y in range(columns): row = row + "{},".format(random.randint(0,1000)); result += row + "\n" 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): 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": {}, "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