s3-tests/s3tests_boto3/functional/test_s3select.py

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