s3-tests/s3tests_boto3/functional/test_s3select.py

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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
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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):
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list_of_int.append(int(col));
col_num+=1;
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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 )
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def test_column_sum_min_max():
csv_obj = create_random_csv_object(10000,10)
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csv_obj_name = "csv_10000x10"
bucket_name = "test"
upload_csv_object(bucket_name,csv_obj_name,csv_obj)
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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)
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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
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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.
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csv_obj = create_random_csv_object(10000,10)
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csv_obj_name = "csv_10000x10"
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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
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# 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,"