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Hi All, | |
I am facing a quite interesting problem. | |
I am trying to implement a new virtual table, everything seems alright, I receive SQLITE_OK code on the registration but as soon as I try to use the vtab that I just created I only get an error: "no such module: $NAME_VTAB" | |
It seems to me that I followed the documentation quite closely, moreover, I am not doing weird cast or particular alchemy with the code, with the exception that it is rust code and not plain C. | |
What I do is quite simple, I just call `sqlite3_create_module_v2` passing all the parameter. |
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Last login: Tue Apr 17 20:40:55 2018 from 90.41.4.210 | |
ubuntu@ip-172-31-14-12:~$ | |
ubuntu@ip-172-31-14-12:~$ | |
ubuntu@ip-172-31-14-12:~$ cd redis-4.0.9/src/ | |
ubuntu@ip-172-31-14-12:~/redis-4.0.9/src$ ./redis-cli | |
127.0.0.1:6379> REDISQL.CREATE_DB DB | |
OK | |
127.0.0.1:6379> REDISQL.EXEC DB "create table test(a int, b int);" | |
1) DONE |
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#include <stdio.h> | |
#include <stdlib.h> | |
#include "hiredis.h" | |
int main() { | |
redisContext *c; | |
redisReply *reply; | |
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/* automatically generated by rust-bindgen */ | |
#[repr(C)] | |
pub struct __BindgenUnionField<T>(::std::marker::PhantomData<T>); | |
impl <T> __BindgenUnionField<T> { | |
#[inline] | |
pub fn new() -> Self { __BindgenUnionField(::std::marker::PhantomData) } | |
#[inline] | |
pub unsafe fn as_ref(&self) -> &T { ::std::mem::transmute(self) } | |
#[inline] |
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extern crate rusqlite; | |
extern crate libsqlite3_sys as sqlite3; | |
use std::io::{self, Read}; | |
use std::path::Path; | |
use std::mem; | |
use std::ptr; | |
use std::ffi::{CString, CStr}; | |
use rusqlite::Connection; |
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| exp IF exp ELSE exp { | |
if ($3.expression_type == IMMEDIATE){ | |
if ($3.value) { | |
$$ = $1; | |
} else { | |
$$ = $5; | |
} | |
} else { | |
t_axe_label* exit = newLabel(program); | |
t_axe_label* else_branch = newLabel(program); |
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=== REDIS BUG REPORT START: Cut & paste starting from here === | |
5867:M 28 Nov 13:28:29.432 # Redis 999.999.999 crashed by signal: 11 | |
5867:M 28 Nov 13:28:29.432 # Crashed running the instuction at: 0x4bf5bc | |
5867:M 28 Nov 13:28:29.432 # Accessing address: 0x200400640 | |
5867:M 28 Nov 13:28:29.432 # Failed assertion: <no assertion failed> (<no file>:0) | |
------ STACK TRACE ------ | |
EIP: | |
./redis-server *:6379(je_malloc_usable_size+0x3c)[0x4bf5bc] |
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sig License{} | |
sig Credential{} | |
sig User { | |
drivingLicense: one License, | |
credential: lone Credential | |
} | |
fact oneLicenseForUser { | |
no l: License, u, u': User | u != u' and l in u.drivingLicense and l in u'.drivingLicense |
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\section*{Abstract} | |
L'esplosione di internet ha portato alla raccolta di un quantitativo di dati mai visto prima; la necessità di analizzare e trarre valore da questa grande quantità di dati ha reso fondamentale l'uso di applicazioni distribuite su più macchine. | |
L'uso di applicazioni distribuite rende però molto difficile stimare il tempo di completamento dei task sottomessi, metrica che invece è di estremo interesse sia per gli utilizzatori del cluster che per chi lo gestisce. | |
In questo lavoro ci siamo concentrati nella analisi del tempo di completamento di job MapReduce eseguiti su Hadoop usando il framework MARC. | |
I risultati ottenuti sono incoraggianti, ma non ancora utilizzabili per ottenere stime reali di tempi di completamento. | |
\section{Introduzione} | |
L'esplosione di internet ha portato alla raccolta di un quantitativo di dati mai visto prima; la necessità di analizzare e trarre valore da questa grande quantità di dati ha reso fondamentale l'uso di applicazioni distribuite su più macchine. |
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slope | phase | maps | blocksize | dimension | start_reduce | reducers | replication | reduce_buffer_io | start_percentage | end_percentage | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|
2 | 0.188338293928771 | 1 | 375 | 133120000 | 4.9e+10 | 5 | 24 | 4 | 100 | 6 | 122 | |
7 | 0.160270615352683 | 1 | 1201 | 33280000 | 3.92e+10 | 50 | 12 | 2 | 100 | 51 | 131 | |
12 | 0.0787062082376971 | 1 | 1802 | 16640000 | 2.94e+10 | 50 | 48 | 2 | 100 | 51 | 111 | |
17 | 0.238429714945174 | 1 | 400 | 99840000 | 3.92e+10 | 5 | 12 | 4 | 100 | 6 | 132 | |
21 | 0.106242737810447 | 1 | 1802 | 16640000 | 2.94e+10 | 50 | 12 | 3 | 100 | 51 | 132 | |
26 | 0.383769653172287 | 1 | 223 | 134217728 | 2.94e+10 | 5 | 6 | 2 | 100 | 6 | 132 | |
31 | 0.158803533013214 | 1 | 372 | 134217728 | 4.9e+10 | 5 | 48 | 4 | 100 | 6 | 114 | |
36 | 0.25298897032558 | 1 | 225 | 133120000 | 2.94e+10 | 35 | 24 | 4 | 100 | 36 | 123 | |
41 | 0.354143534161834 | 1 | 223 | 134217728 | 2.94e+10 | 5 | 12 | 4 | 100 | 6 | 131 |