# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You 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.

import json
import os.path
import random
import signal
import time

import requests
from ducktape.errors import DucktapeError
from ducktape.services.service import Service
from ducktape.utils.util import wait_until

from kafkatest.directory_layout.kafka_path import KafkaPathResolverMixin


class ConnectServiceBase(KafkaPathResolverMixin, Service):
    """Base class for Kafka Connect services providing some common settings and functionality"""

    PERSISTENT_ROOT = "/mnt/connect"
    CONFIG_FILE = os.path.join(PERSISTENT_ROOT, "connect.properties")
    # The log file contains normal log4j logs written using a file appender. stdout and stderr are handled separately
    # so they can be used for other output, e.g. verifiable source & sink.
    LOG_FILE = os.path.join(PERSISTENT_ROOT, "connect.log")
    STDOUT_FILE = os.path.join(PERSISTENT_ROOT, "connect.stdout")
    STDERR_FILE = os.path.join(PERSISTENT_ROOT, "connect.stderr")
    LOG4J_CONFIG_FILE = os.path.join(PERSISTENT_ROOT, "connect-log4j.properties")
    PID_FILE = os.path.join(PERSISTENT_ROOT, "connect.pid")
    EXTERNAL_CONFIGS_FILE = os.path.join(PERSISTENT_ROOT, "connect-external-configs.properties")
    CONNECT_REST_PORT = 8083
    HEAP_DUMP_FILE = os.path.join(PERSISTENT_ROOT, "connect_heap_dump.bin")

    # Currently the Connect worker supports waiting on three modes:
    STARTUP_MODE_INSTANT = 'INSTANT'
    """STARTUP_MODE_INSTANT: Start Connect worker and return immediately"""
    STARTUP_MODE_LOAD = 'LOAD'
    """STARTUP_MODE_LOAD: Start Connect worker and return after discovering and loading plugins"""
    STARTUP_MODE_LISTEN = 'LISTEN'
    """STARTUP_MODE_LISTEN: Start Connect worker and return after opening the REST port."""

    logs = {
        "connect_log": {
            "path": LOG_FILE,
            "collect_default": True},
        "connect_stdout": {
            "path": STDOUT_FILE,
            "collect_default": False},
        "connect_stderr": {
            "path": STDERR_FILE,
            "collect_default": True},
        "connect_heap_dump_file": {
            "path": HEAP_DUMP_FILE,
            "collect_default": True}
    }

    def __init__(self, context, num_nodes, kafka, files, startup_timeout_sec = 60):
        super(ConnectServiceBase, self).__init__(context, num_nodes)
        self.kafka = kafka
        self.security_config = kafka.security_config.client_config()
        self.files = files
        self.startup_mode = self.STARTUP_MODE_LISTEN
        self.startup_timeout_sec = startup_timeout_sec
        self.environment = {}
        self.external_config_template_func = None

    def pids(self, node):
        """Return process ids for Kafka Connect processes."""
        try:
            return [pid for pid in node.account.ssh_capture("cat " + self.PID_FILE, callback=int)]
        except:
            return []

    def set_configs(self, config_template_func, connector_config_templates=None):
        """
        Set configurations for the worker and the connector to run on
        it. These are not provided in the constructor because the worker
        config generally needs access to ZK/Kafka services to
        create the configuration.
        """
        self.config_template_func = config_template_func
        self.connector_config_templates = connector_config_templates

    def set_external_configs(self, external_config_template_func):
        """
        Set the properties that will be written in the external file properties
        as used by the org.apache.kafka.common.config.provider.FileConfigProvider.
        When this is used, the worker configuration must also enable the FileConfigProvider.
        This is not provided in the constructor in case the worker
        config generally needs access to ZK/Kafka services to
        create the configuration.
        """
        self.external_config_template_func = external_config_template_func

    def listening(self, node):
        try:
            self.list_connectors(node)
            self.logger.debug("Connect worker started serving REST at: '%s:%s')", node.account.hostname,
                              self.CONNECT_REST_PORT)
            return True
        except requests.exceptions.ConnectionError:
            self.logger.debug("REST resources are not loaded yet")
            return False

    def start(self, mode=STARTUP_MODE_LISTEN):
        self.startup_mode = mode
        super(ConnectServiceBase, self).start()

    def start_and_return_immediately(self, node, worker_type, remote_connector_configs):
        cmd = self.start_cmd(node, remote_connector_configs)
        self.logger.debug("Connect %s command: %s", worker_type, cmd)
        node.account.ssh(cmd)

    def start_and_wait_to_load_plugins(self, node, worker_type, remote_connector_configs):
        with node.account.monitor_log(self.LOG_FILE) as monitor:
            self.start_and_return_immediately(node, worker_type, remote_connector_configs)
            monitor.wait_until('Kafka version', timeout_sec=self.startup_timeout_sec,
                               err_msg="Never saw message indicating Kafka Connect finished startup on node: " +
                                       "%s in condition mode: %s" % (str(node.account), self.startup_mode))

    def start_and_wait_to_start_listening(self, node, worker_type, remote_connector_configs):
        self.start_and_return_immediately(node, worker_type, remote_connector_configs)
        wait_until(lambda: self.listening(node), timeout_sec=self.startup_timeout_sec,
                   err_msg="Kafka Connect failed to start on node: %s in condition mode: %s" %
                   (str(node.account), self.startup_mode))

    def stop_node(self, node, clean_shutdown=True):
        self.logger.info((clean_shutdown and "Cleanly" or "Forcibly") + " stopping Kafka Connect on " + str(node.account))
        pids = self.pids(node)
        sig = signal.SIGTERM if clean_shutdown else signal.SIGKILL

        for pid in pids:
            node.account.signal(pid, sig, allow_fail=True)
        if clean_shutdown:
            for pid in pids:
                wait_until(lambda: not node.account.alive(pid), timeout_sec=self.startup_timeout_sec, err_msg="Kafka Connect process on " + str(
                    node.account) + " took too long to exit")

        node.account.ssh("rm -f " + self.PID_FILE, allow_fail=False)

    def restart(self, clean_shutdown=True):
        # We don't want to do any clean up here, just restart the process.
        for node in self.nodes:
            self.logger.info("Restarting Kafka Connect on " + str(node.account))
            self.restart_node(node, clean_shutdown)

    def restart_node(self, node, clean_shutdown=True):
        self.stop_node(node, clean_shutdown)
        self.start_node(node)

    def clean_node(self, node):
        node.account.kill_process("connect", clean_shutdown=False, allow_fail=True)
        self.security_config.clean_node(node)
        other_files = " ".join(self.config_filenames() + self.files)
        node.account.ssh("rm -rf -- %s %s" % (ConnectServiceBase.PERSISTENT_ROOT, other_files), allow_fail=False)

    def config_filenames(self):
        return [os.path.join(self.PERSISTENT_ROOT, "connect-connector-" + str(idx) + ".properties") for idx, template in enumerate(self.connector_config_templates or [])]

    def list_connectors(self, node=None, **kwargs):
        return self._rest_with_retry('/connectors', node=node, **kwargs)

    def create_connector(self, config, node=None, **kwargs):
        create_request = {
            'name': config['name'],
            'config': config
        }
        return self._rest_with_retry('/connectors', create_request, node=node, method="POST", **kwargs)

    def get_connector(self, name, node=None, **kwargs):
        return self._rest_with_retry('/connectors/' + name, node=node, **kwargs)

    def get_connector_config(self, name, node=None, **kwargs):
        return self._rest_with_retry('/connectors/' + name + '/config', node=node, **kwargs)

    def set_connector_config(self, name, config, node=None, **kwargs):
        # Unlike many other calls, a 409 when setting a connector config is expected if the connector already exists.
        # However, we also might see 409s for other reasons (e.g. rebalancing). So we still perform retries at the cost
        # of tests possibly taking longer to ultimately fail. Tests that care about this can explicitly override the
        # number of retries.
        return self._rest_with_retry('/connectors/' + name + '/config', config, node=node, method="PUT", **kwargs)

    def get_connector_tasks(self, name, node=None, **kwargs):
        return self._rest_with_retry('/connectors/' + name + '/tasks', node=node, **kwargs)

    def delete_connector(self, name, node=None, **kwargs):
        return self._rest_with_retry('/connectors/' + name, node=node, method="DELETE", **kwargs)

    def get_connector_status(self, name, node=None):
        return self._rest('/connectors/' + name + '/status', node=node)

    def restart_connector(self, name, node=None, **kwargs):
        return self._rest_with_retry('/connectors/' + name + '/restart', node=node, method="POST", **kwargs)

    def restart_task(self, connector_name, task_id, node=None):
        return self._rest('/connectors/' + connector_name + '/tasks/' + str(task_id) + '/restart', node=node, method="POST")

    def pause_connector(self, name, node=None):
        return self._rest('/connectors/' + name + '/pause', node=node, method="PUT")

    def resume_connector(self, name, node=None):
        return self._rest('/connectors/' + name + '/resume', node=node, method="PUT")

    def list_connector_plugins(self, node=None):
        return self._rest('/connector-plugins/', node=node)

    def validate_config(self, connector_type, validate_request, node=None):
        return self._rest('/connector-plugins/' + connector_type + '/config/validate', validate_request, node=node, method="PUT")

    def _rest(self, path, body=None, node=None, method="GET"):
        if node is None:
            node = random.choice(self.nodes)

        meth = getattr(requests, method.lower())
        url = self._base_url(node) + path
        self.logger.debug("Kafka Connect REST request: %s %s %s %s", node.account.hostname, url, method, body)
        resp = meth(url, json=body)
        self.logger.debug("%s %s response: %d", url, method, resp.status_code)
        if resp.status_code > 400:
            self.logger.debug("Connect REST API error for %s: %d %s", resp.url, resp.status_code, resp.text)
            raise ConnectRestError(resp.status_code, resp.text, resp.url)
        if resp.status_code == 204 or resp.status_code == 202:
            return None
        else:
            return resp.json()

    def _rest_with_retry(self, path, body=None, node=None, method="GET", retries=40, retry_backoff=.25):
        """
        Invokes a REST API with retries for errors that may occur during normal operation (notably 409 CONFLICT
        responses that can occur due to rebalancing or 404 when the connect resources are not initialized yet).
        """
        exception_to_throw = None
        for i in range(0, retries + 1):
            try:
                return self._rest(path, body, node, method)
            except ConnectRestError as e:
                exception_to_throw = e
                if e.status != 409 and e.status != 404:
                    break
                time.sleep(retry_backoff)
        raise exception_to_throw

    def _base_url(self, node):
        return 'http://' + node.account.externally_routable_ip + ':' + str(self.CONNECT_REST_PORT)

    def append_to_environment_variable(self, envvar, value):
        env_opts = self.environment[envvar]
        if env_opts is None:
            env_opts = "\"%s\"" % value
        else:
            env_opts = "\"%s %s\"" % (env_opts.strip('\"'), value)
        self.environment[envvar] = env_opts


class ConnectStandaloneService(ConnectServiceBase):
    """Runs Kafka Connect in standalone mode."""

    def __init__(self, context, kafka, files, startup_timeout_sec = 60):
        super(ConnectStandaloneService, self).__init__(context, 1, kafka, files, startup_timeout_sec)

    # For convenience since this service only makes sense with a single node
    @property
    def node(self):
        return self.nodes[0]

    def start_cmd(self, node, connector_configs):
        cmd = "( export KAFKA_LOG4J_OPTS=\"-Dlog4j.configuration=file:%s\"; " % self.LOG4J_CONFIG_FILE
        heap_kafka_opts = "-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=%s" % \
                          self.logs["connect_heap_dump_file"]["path"]
        other_kafka_opts = self.security_config.kafka_opts.strip('\"')
        cmd += "export KAFKA_OPTS=\"%s %s\"; " % (heap_kafka_opts, other_kafka_opts)
        for envvar in self.environment:
            cmd += "export %s=%s; " % (envvar, str(self.environment[envvar]))
        cmd += "%s %s " % (self.path.script("connect-standalone.sh", node), self.CONFIG_FILE)
        cmd += " ".join(connector_configs)
        cmd += " & echo $! >&3 ) 1>> %s 2>> %s 3> %s" % (self.STDOUT_FILE, self.STDERR_FILE, self.PID_FILE)
        return cmd

    def start_node(self, node):
        node.account.ssh("mkdir -p %s" % self.PERSISTENT_ROOT, allow_fail=False)

        self.security_config.setup_node(node)
        if self.external_config_template_func:
            node.account.create_file(self.EXTERNAL_CONFIGS_FILE, self.external_config_template_func(node))
        node.account.create_file(self.CONFIG_FILE, self.config_template_func(node))
        node.account.create_file(self.LOG4J_CONFIG_FILE, self.render('connect_log4j.properties', log_file=self.LOG_FILE))
        remote_connector_configs = []
        for idx, template in enumerate(self.connector_config_templates):
            target_file = os.path.join(self.PERSISTENT_ROOT, "connect-connector-" + str(idx) + ".properties")
            node.account.create_file(target_file, template)
            remote_connector_configs.append(target_file)

        self.logger.info("Starting Kafka Connect standalone process on " + str(node.account))
        if self.startup_mode == self.STARTUP_MODE_LOAD:
            self.start_and_wait_to_load_plugins(node, 'standalone', remote_connector_configs)
        elif self.startup_mode == self.STARTUP_MODE_INSTANT:
            self.start_and_return_immediately(node, 'standalone', remote_connector_configs)
        else:
            # The default mode is to wait until the complete startup of the worker
            self.start_and_wait_to_start_listening(node, 'standalone', remote_connector_configs)

        if len(self.pids(node)) == 0:
            raise RuntimeError("No process ids recorded")


class ConnectDistributedService(ConnectServiceBase):
    """Runs Kafka Connect in distributed mode."""

    def __init__(self, context, num_nodes, kafka, files, offsets_topic="connect-offsets",
                 configs_topic="connect-configs", status_topic="connect-status", startup_timeout_sec = 60):
        super(ConnectDistributedService, self).__init__(context, num_nodes, kafka, files, startup_timeout_sec)
        self.offsets_topic = offsets_topic
        self.configs_topic = configs_topic
        self.status_topic = status_topic

    # connector_configs argument is intentionally ignored in distributed service.
    def start_cmd(self, node, connector_configs):
        cmd = "( export KAFKA_LOG4J_OPTS=\"-Dlog4j.configuration=file:%s\"; " % self.LOG4J_CONFIG_FILE
        heap_kafka_opts = "-XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=%s" % \
                          self.logs["connect_heap_dump_file"]["path"]
        other_kafka_opts = self.security_config.kafka_opts.strip('\"')
        cmd += "export KAFKA_OPTS=\"%s %s\"; " % (heap_kafka_opts, other_kafka_opts)
        for envvar in self.environment:
            cmd += "export %s=%s; " % (envvar, str(self.environment[envvar]))
        cmd += "%s %s " % (self.path.script("connect-distributed.sh", node), self.CONFIG_FILE)
        cmd += " & echo $! >&3 ) 1>> %s 2>> %s 3> %s" % (self.STDOUT_FILE, self.STDERR_FILE, self.PID_FILE)
        return cmd

    def start_node(self, node):
        node.account.ssh("mkdir -p %s" % self.PERSISTENT_ROOT, allow_fail=False)

        self.security_config.setup_node(node)
        if self.external_config_template_func:
            node.account.create_file(self.EXTERNAL_CONFIGS_FILE, self.external_config_template_func(node))
        node.account.create_file(self.CONFIG_FILE, self.config_template_func(node))
        node.account.create_file(self.LOG4J_CONFIG_FILE, self.render('connect_log4j.properties', log_file=self.LOG_FILE))
        if self.connector_config_templates:
            raise DucktapeError("Config files are not valid in distributed mode, submit connectors via the REST API")

        self.logger.info("Starting Kafka Connect distributed process on " + str(node.account))
        if self.startup_mode == self.STARTUP_MODE_LOAD:
            self.start_and_wait_to_load_plugins(node, 'distributed', '')
        elif self.startup_mode == self.STARTUP_MODE_INSTANT:
            self.start_and_return_immediately(node, 'distributed', '')
        else:
            # The default mode is to wait until the complete startup of the worker
            self.start_and_wait_to_start_listening(node, 'distributed', '')

        if len(self.pids(node)) == 0:
            raise RuntimeError("No process ids recorded")


class ErrorTolerance(object):
    ALL = "all"
    NONE = "none"


class ConnectRestError(RuntimeError):
    def __init__(self, status, msg, url):
        self.status = status
        self.message = msg
        self.url = url

    def __unicode__(self):
        return "Kafka Connect REST call failed: returned " + self.status + " for " + self.url + ". Response: " + self.message


class VerifiableConnector(object):
    def messages(self):
        """
        Collect and parse the logs from Kafka Connect nodes. Return a list containing all parsed JSON messages generated by
        this source.
        """
        self.logger.info("Collecting messages from log of %s %s", type(self).__name__, self.name)
        records = []
        for node in self.cc.nodes:
            for line in node.account.ssh_capture('cat ' + self.cc.STDOUT_FILE):
                try:
                    data = json.loads(line)
                except ValueError:
                    self.logger.debug("Ignoring unparseable line: %s", line)
                    continue
                # Filter to only ones matching our name to support multiple verifiable producers
                if data['name'] != self.name:
                    continue
                data['node'] = node
                records.append(data)
        return records

    def stop(self):
        self.logger.info("Destroying connector %s %s", type(self).__name__, self.name)
        self.cc.delete_connector(self.name)


class VerifiableSource(VerifiableConnector):
    """
    Helper class for running a verifiable source connector on a Kafka Connect cluster and analyzing the output.
    """

    def __init__(self, cc, name="verifiable-source", tasks=1, topic="verifiable", throughput=1000):
        self.cc = cc
        self.logger = self.cc.logger
        self.name = name
        self.tasks = tasks
        self.topic = topic
        self.throughput = throughput

    def committed_messages(self):
        return filter(lambda m: 'committed' in m and m['committed'], self.messages())

    def sent_messages(self):
        return filter(lambda m: 'committed' not in m or not m['committed'], self.messages())

    def start(self):
        self.logger.info("Creating connector VerifiableSourceConnector %s", self.name)
        self.cc.create_connector({
            'name': self.name,
            'connector.class': 'org.apache.kafka.connect.tools.VerifiableSourceConnector',
            'tasks.max': self.tasks,
            'topic': self.topic,
            'throughput': self.throughput
        })


class VerifiableSink(VerifiableConnector):
    """
    Helper class for running a verifiable sink connector on a Kafka Connect cluster and analyzing the output.
    """

    def __init__(self, cc, name="verifiable-sink", tasks=1, topics=["verifiable"]):
        self.cc = cc
        self.logger = self.cc.logger
        self.name = name
        self.tasks = tasks
        self.topics = topics

    def flushed_messages(self):
        return filter(lambda m: 'flushed' in m and m['flushed'], self.messages())

    def received_messages(self):
        return filter(lambda m: 'flushed' not in m or not m['flushed'], self.messages())

    def start(self):
        self.logger.info("Creating connector VerifiableSinkConnector %s", self.name)
        self.cc.create_connector({
            'name': self.name,
            'connector.class': 'org.apache.kafka.connect.tools.VerifiableSinkConnector',
            'tasks.max': self.tasks,
            'topics': ",".join(self.topics)
        })

class MockSink(object):

    def __init__(self, cc, topics, mode=None, delay_sec=10, name="mock-sink"):
        self.cc = cc
        self.logger = self.cc.logger
        self.name = name
        self.mode = mode
        self.delay_sec = delay_sec
        self.topics = topics

    def start(self):
        self.logger.info("Creating connector MockSinkConnector %s", self.name)
        self.cc.create_connector({
            'name': self.name,
            'connector.class': 'org.apache.kafka.connect.tools.MockSinkConnector',
            'tasks.max': 1,
            'topics': ",".join(self.topics),
            'mock_mode': self.mode,
            'delay_ms': self.delay_sec * 1000
        })

class MockSource(object):

    def __init__(self, cc, mode=None, delay_sec=10, name="mock-source"):
        self.cc = cc
        self.logger = self.cc.logger
        self.name = name
        self.mode = mode
        self.delay_sec = delay_sec

    def start(self):
        self.logger.info("Creating connector MockSourceConnector %s", self.name)
        self.cc.create_connector({
            'name': self.name,
            'connector.class': 'org.apache.kafka.connect.tools.MockSourceConnector',
            'tasks.max': 1,
            'mock_mode': self.mode,
            'delay_ms': self.delay_sec * 1000
        })
