text: # Copyright 2013-2015 DataStax, Inc.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  # http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  
  from heapq import heappush, heappop
  from itertools import cycle
  import six
  from six.moves import xrange, zip
  from threading import Condition
  import sys
  
  from cassandra.cluster import PagedResult
  
  import logging
  log = logging.getLogger(__name__)
  
  def execute_concurrent(session, statements_and_parameters, concurrency=100, raise_on_first_error=True, results_generator=False):
      """
      Executes a sequence of (statement, parameters) tuples concurrently.  Each
      ``parameters`` item must be a sequence or :const:`None`.
  
      The `concurrency` parameter controls how many statements will be executed
      concurrently.  When :attr:`.Cluster.protocol_version` is set to 1 or 2,
      it is recommended that this be kept below 100 times the number of
      core connections per host times the number of connected hosts (see
      :meth:`.Cluster.set_core_connections_per_host`).  If that amount is exceeded,
      the event loop thread may attempt to block on new connection creation,
      substantially impacting throughput.  If :attr:`~.Cluster.protocol_version`
      is 3 or higher, you can safely experiment with higher levels of concurrency.
  
      If `raise_on_first_error` is left as :const:`True`, execution will stop
      after the first failed statement and the corresponding exception will be
      raised.
  
      `results_generator` controls how the results are returned.
  
          If :const:`False`, the results are returned only after all requests have completed.
  
          If :const:`True`, a generator expression is returned. Using a generator results in a constrained
          memory footprint when the results set will be large -- results are yielded
          as they return instead of materializing the entire list at once. The trade for lower memory
          footprint is marginal CPU overhead (more thread coordination and sorting out-of-order results
          on-the-fly).
  
      A sequence of ``(success, result_or_exc)`` tuples is returned in the same
      order that the statements were passed in.  If ``success`` is :const:`False`,
      there was an error executing the statement, and ``result_or_exc`` will be
      an :class:`Exception`.  If ``success`` is :const:`True`, ``result_or_exc``
      will be the query result.
  
      Example usage::
  
          select_statement = session.prepare("SELECT * FROM users WHERE id=?")
  
          statements_and_params = []
          for user_id in user_ids:
              params = (user_id, )
              statements_and_params.append((select_statement, params))
  
          results = execute_concurrent(
              session, statements_and_params, raise_on_first_error=False)
  
          for (success, result) in results:
              if not success:
                  handle_error(result)  # result will be an Exception
              else:
                  process_user(result[0])  # result will be a list of rows
  
      """
      if concurrency <= 0:
          raise ValueError("concurrency must be greater than 0")
  
      if not statements_and_parameters:
          return []
  
      executor = ConcurrentExecutorGenResults(session, statements_and_parameters) if results_generator else ConcurrentExecutorListResults(session, statements_and_parameters)
      return executor.execute(concurrency, raise_on_first_error)
  
  
  class _ConcurrentExecutor(object):
  
      def __init__(self, session, statements_and_params):
          self.session = session
          self._enum_statements = enumerate(iter(statements_and_params))
          self._condition = Condition()
          self._fail_fast = False
          self._results_queue = []
          self._current = 0
          self._exec_count = 0
  
      def execute(self, concurrency, fail_fast):
          self._fail_fast = fail_fast
          self._results_queue = []
          self._current = 0
          self._exec_count = 0
          with self._condition:
              for n in xrange(concurrency):
                  if not self._execute_next():
                      break
          return self._results()
  
      def _execute_next(self):
          # lock must be held
          try:
              (idx, (statement, params)) = next(self._enum_statements)
              self._exec_count += 1
              self._execute(idx, statement, params)
              return True
          except StopIteration:
              pass
  
      def _execute(self, idx, statement, params):
          try:
              future = self.session.execute_async(statement, params, timeout=None)
              args = (future, idx)
              future.add_callbacks(
                  callback=self._on_success, callback_args=args,
                  errback=self._on_error, errback_args=args)
          except Exception as exc:
              # exc_info with fail_fast to preserve stack trace info when raising on the client thread
              # (matches previous behavior -- not sure why we wouldn't want stack trace in the other case)
              e = sys.exc_info() if self._fail_fast and six.PY2 else exc
              self._put_result(e, idx, False)
  
      def _on_success(self, result, future, idx):
          if future.has_more_pages:
              result = PagedResult(future, result)
              future.clear_callbacks()
          self._put_result(result, idx, True)
  
      def _on_error(self, result, future, idx):
          self._put_result(result, idx, False)
  
      @staticmethod
      def _raise(exc):
          if six.PY2 and isinstance(exc, tuple):
              (exc_type, value, traceback) = exc
              six.reraise(exc_type, value, traceback)
          else:
              raise exc
  
  
  class ConcurrentExecutorGenResults(_ConcurrentExecutor):
  
      def _put_result(self, result, idx, success):
          with self._condition:
              heappush(self._results_queue, (idx, (success, result)))
              self._execute_next()
              self._condition.notify()
  
      def _results(self):
          with self._condition:
              while self._current < self._exec_count:
                  while not self._results_queue or self._results_queue[0][0] != self._current:
                      self._condition.wait()
                  while self._results_queue and self._results_queue[0][0] == self._current:
                      _, res = heappop(self._results_queue)
                      try:
                          self._condition.release()
                          if self._fail_fast and not res[0]:
                              self._raise(res[1])
                          yield res
                      finally:
                          self._condition.acquire()
                      self._current += 1
  
  
  class ConcurrentExecutorListResults(_ConcurrentExecutor):
  
      _exception = None
  
      def execute(self, concurrency, fail_fast):
          self._exception = None
          return super(ConcurrentExecutorListResults, self).execute(concurrency, fail_fast)
  
      def _put_result(self, result, idx, success):
          self._results_queue.append((idx, (success, result)))
          with self._condition:
              self._current += 1
              if not success and self._fail_fast:
                  if not self._exception:
                      self._exception = result
                  self._condition.notify()
              elif not self._execute_next() and self._current == self._exec_count:
                  self._condition.notify()
  
      def _results(self):
          with self._condition:
              while self._current < self._exec_count:
                  self._condition.wait()
                  if self._exception and self._fail_fast:
                      self._raise(self._exception)
          return [r[1] for r in sorted(self._results_queue)]
  
  
  
  def execute_concurrent_with_args(session, statement, parameters, *args, **kwargs):
      """
      Like :meth:`~cassandra.concurrent.execute_concurrent()`, but takes a single
      statement and a sequence of parameters.  Each item in ``parameters``
      should be a sequence or :const:`None`.
  
      Example usage::
  
          statement = session.prepare("INSERT INTO mytable (a, b) VALUES (1, ?)")
          parameters = [(x,) for x in range(1000)]
          execute_concurrent_with_args(session, statement, parameters, concurrency=50)
      """
      return execute_concurrent(session, zip(cycle((statement,)), parameters), *args, **kwargs)
  