coffeemug

/* This program demonstrates a bug in the Linux kernel version 3.2.0 using the
`ext4` filesystem.
 
Steps to compile:
 
    $ gcc -o demo demo.c -laio
 
Steps to reproduce:
 
1. Run `./demo FILE`, where `FILE` is the path where the program will put the

coffeemug

test

coffeemug

r.table(Build.__tablename__).get(build_id).update({'result': r.table(Build.__tablename__).get(build_id)['result'].append(line)}).run()

coffeemug

r.table(Build.__tablename__).get(build_id).update({'result': r['result'].append(line)}).run()

coffeemug

--------------------------------------------------------------------------------
  n        time(i)         total(B)   useful-heap(B) extra-heap(B)    stacks(B)
--------------------------------------------------------------------------------
 78 57,030,430,673    1,440,292,888    1,227,094,500   213,198,388            0
85.20% (1,227,094,500B) (heap allocation functions) malloc/new/new[], --alloc-fns, etc.
->26.62% (383,410,176B) 0x207EA0D: malloc_aligned(unsigned long, unsigned long) (utils.cc:234)
| ->13.94% (200,802,304B) 0x186277E: artificial_stack_t::artificial_stack_t(void (*)(), unsigned long) (context_switching.cc:37)
| | ->13.94% (200,802,304B) 0x1862F4D: coro_t::coro_t() (coroutines.cc:127)
| |   ->13.94% (200,802,304B) 0x1863DAA: coro_t::get_coro() (coroutines.cc:356)
| |     ->06.41% (92,274,688B) 0x18BD37A: coro_t* coro_t::get_and_init_coro<boost::_bi::bind_t<void, boost::_mfi::mf2<void, mc_inner_buf_t, bool, file_account_t*>, boost::_bi::list3<boost::_bi::value<mc_inner_buf_t*>, boost::_bi::valu

coffeemug

You can import data as follows:

# Import a JSON document into table `users` in database `my_db`
$ rethinkdb import -c HOST:PORT -f user_data.json --table my_db.users

# Import a CSV document
$ rethinkdb import -c HOST:PORT -f user_data.csv --format csv --table my_db.users

coffeemug

Suppose you have a number of nodes on a network that spin up cron jobs to perform various tasks. However, you need the nodes to cooperate to ensure that multiple nodes don't spin up the same task. You can easily implement this functionality on top of RethinkDB as follows:

// A single node atomically pushes jobs onto an array in the database
r.table('admin').get('jobs').update({ job_list: r.row('job_list').append(JOB_DESCRIPTION)) })

coffeemug

The getField command now works on sequences

In the previous versions of RethinkDB you could get a subset of an object using the pluck command, and the value of a specific field using the getField command (accessible via () in Javascript and [] in Python and Ruby):

r.expr({a: 1, b: 1}).pluck('a')
// returns {a: 1}

coffeemug

Querying by multiple keys

The previous releases of RethinkDB allowed querying indexes as follows:

// Three ways to get the user with primary key 5
r.table('users').get(5)
r.table('users').getAll(5)
r.table('users').getAll(5, {index: 'id'})

coffeemug

Syntax for plucking nested objects

In the previous versions of RethinkDB you could use the pluck command to extract only specific attributes from an object or a sequence of objects:

r.expr({a: 1, b: {c: 1, d: 1}}).pluck('b')
// returns `b: {c: 1, d: 1}`