Пример #1
0
    def execute(self, context):
        from depc.utils import get_start_end_ts

        self.logger.info("Excluded nodes for {label}: {excluded}".format(
            label=self.label, excluded=self.excluded_nodes_from_average))
        if self.excluded_nodes_from_average:
            redis_key = "{team}.{label}.excluded_nodes_from_label_average".format(
                team=self.team_name, label=self.label)
            redis.delete(redis_key)
            redis.rpush(redis_key, *self.excluded_nodes_from_average)

        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        # Save the total number of nodes in this label
        self.logger.info(
            "[{team}/{label}] Label contains {count} nodes".format(
                team=self.team_name, label=self.label, count=self.count))
        self.write_metric(
            metric="depc.qos.stats",
            ts=start,
            value=self.count,
            tags={
                "team": self.team_id,
                "label": self.label,
                "type": "total"
            },
        )

        # We'll use the AfterSubdagOperator to compute
        # some statistics using xcom.
        return {"count": self.count, "start_time": time.time()}
Пример #2
0
    def execute(self, context):
        from depc.controllers import NotFoundError
        from depc.controllers.worst import WorstController
        from depc.models.worst import Periods
        from depc.utils import get_start_end_ts
        from depc.utils.warp10 import Warp10Client

        # get the right start and end with the date of the DAG
        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        with self.app.app_context():
            client = Warp10Client(use_cache=True)
            client.generate_script(
                WORST_ITEMS_PER_LABEL,
                start,
                end,
                max_gts=MAX_DATAPOINTS,
                extra_params={
                    "team": self.team_id,
                    "label": self.label,
                    "count": str(MAX_WORST_ITEMS),
                },
            )
            start = time.time()
            results = client.execute()
            self.log.info("Warp10 script took {}s".format(
                round(time.time() - start, 3)))

            # produce the data for the relational database
            worst_items = {}
            for d in results[0]:
                qos = d["v"][0][1]
                if qos < 100:
                    worst_items[d["l"]["name"]] = qos

            nb_worst_items = len(worst_items)
            if nb_worst_items:
                self.log.info("Worst: {} item(s)".format(nb_worst_items))

                metadata = {
                    "team_id": self.team_id,
                    "label": self.label,
                    "period": Periods.daily,
                    "date": ds,
                }

                try:
                    WorstController.update(data={"data": worst_items},
                                           filters={"Worst": metadata})
                except NotFoundError:
                    payload = {"data": worst_items}
                    payload.update(metadata)
                    WorstController.create(payload)
            else:
                self.log.info("No QOS under 100%")
Пример #3
0
    def execute(self, context):
        """
        This task computes the average QOS for a label, using a
        special key in Redis populated by the chunks.
        """
        from depc.extensions import redis_scheduler as redis
        from depc.utils import get_start_end_ts

        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        # Get the list of QOS for the label
        key = "{ds}.{team}.{label}.average".format(ds=ds,
                                                   team=self.team_name,
                                                   label=self.label)
        all_qos = [float(qos) for qos in redis.lrange(key, 0, -1)]

        if not all_qos:
            self.log.critical("No QOS found for any {}, aborting.".format(
                self.label))
            return

        self.log.info(
            "[{0}/{1}] Computing the average QOS using {2} items...".format(
                self.team_name, self.label, len(all_qos)))

        # Let's Numpy computes the average
        avg_qos = np.mean(all_qos)

        self.log.info("[{0}/{1}] The average QOS is {2}%".format(
            self.team_name, self.label, avg_qos))

        # Saving to Beamium
        self.write_metric(
            metric="depc.qos.label",
            ts=start,
            value=avg_qos,
            tags={
                "name": self.label,
                "team": self.team_id
            },
        )
Пример #4
0
    def execute(self, context):
        from depc.utils import get_start_end_ts

        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        # Save the total number of nodes in this label
        self.logger.info(
            "[{team}/{label}] Label contains {count} nodes".format(
                team=self.team_name, label=self.label, count=self.count))
        self.write_metric(
            metric="depc.qos.stats",
            ts=start,
            value=self.count,
            tags={
                "team": self.team_id,
                "label": self.label,
                "type": "total"
            },
        )

        # We'll use the AfterSubdagOperator to compute
        # some statistics using xcom.
        return {"count": self.count, "start_time": time.time()}
Пример #5
0
    def execute(self, context):
        from depc.controllers import NotFoundError
        from depc.controllers.rules import RuleController
        from depc.extensions import redis_scheduler as redis
        from depc.utils import get_start_end_ts

        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        with self.app.app_context():

            # Get the nodes for this team and this label
            query = ("MATCH(n:{label}) RETURN n AS Node "
                     "ORDER BY Node.name "
                     "SKIP {skip} LIMIT {limit}")
            query = query.format(label=self.full_label,
                                 skip=self.skip,
                                 limit=int(self.length))

            records = get_records(query)
            nodes = [dict(record.get("Node").items()) for record in records]

            # Remove old nodes
            nodes = [n for n in nodes if is_active_node(start, end, n)]

            # Get the rule associated to the label for this team
            try:
                rule = RuleController.get(filters={
                    "Rule": {
                        "name": self.rule_name,
                        "team_id": self.team_id
                    }
                })
            except NotFoundError:
                self.log.warning(
                    "[{0}] The label {1} has no associated rule in DEPC".
                    format(self.team_name, self.label))
                return False

            has_qos = False
            auto_fill = check_enable_auto_fill(rule["id"], self.team_id)
            for node in nodes:
                result = RuleController.execute(
                    rule_id=rule["id"],
                    auto_fill=auto_fill,
                    name=node["name"],
                    start=start,
                    end=end,
                )

                if result["qos"]["qos"] != "unknown":
                    has_qos = True
                    self.log.info("[{0}/{1}] The QOS of {2} is {3}%".format(
                        self.team_name,
                        self.label,
                        node["name"],
                        result["qos"]["qos"],
                    ))

                    # Saving to Beamium
                    self.write_metric(
                        metric="depc.qos.node",
                        ts=start,
                        value=result["qos"]["qos"],
                        tags={
                            "label": self.label,
                            "name": node["name"],
                            "team": self.team_id,
                        },
                    )

                    # Used for average computing
                    key = "{ds}.{team}.{label}".format(ds=ds,
                                                       team=self.team_name,
                                                       label=self.label)

                    if not self.excluded_from_label_average(
                            self.team_name, self.label, node["name"]):
                        redis.zadd("{}.sorted".format(key), node["name"],
                                   result["qos"]["qos"])

                    # Save information to reuse it later (`bools_dps` is used in
                    # OperationOperator and `qos` is used in AggregationOperator)
                    redis.set(
                        "{}.{}.node".format(key, node["name"]),
                        json.dumps({
                            "bools_dps": result["qos"]["bools_dps"],
                            "qos": result["qos"]["qos"],
                        }),
                    )

                else:
                    self.log.warning("[{0}/{1}] No QOS for {2}".format(
                        self.team_name, self.label, node["name"]))

                    # Add it in redis to compute some stats in AfterSubdagOperator
                    redis.sadd(
                        "{ds}.{team}.{label}.noqos".format(ds=ds,
                                                           team=self.team_name,
                                                           label=self.label),
                        node["name"],
                    )

            if not has_qos:
                self.log.warning("[{0}/{1}] No QOS found for any items".format(
                    self.team_name, self.label))
Пример #6
0
    def execute(self, context):
        from depc.extensions import redis_scheduler as redis
        from depc.utils import get_start_end_ts

        ds = context["ds"]
        start, end = get_start_end_ts(ds)
        name, dependencies, query = self.build_query()

        self.log.info(
            "[{team}/{label}] Fetching nodes and its dependencies using the following query : {query}"
            .format(team=self.team_name, label=self.label, query=query))

        # Retrieve the node and its dependencies
        start_time = time.time()
        with self.app.app_context():
            records = get_records(query)
        nodes = self.filter_records(
            start=start,
            end=end,
            records=[r for r in records],
            name=name,
            dependencies=dependencies,
        )

        # No node has dependency
        if not nodes:
            self.log.warning("[{team}/{label}] No node has dependency.".format(
                team=self.team_name, label=self.label))
            return

        self.log.info(
            "[{team}/{label}] Nodes fetched in {t}s, processing it...".format(
                team=self.team_name,
                label=self.label,
                t=round(time.time() - start_time, 3),
            ))

        # Process the nodes and remove the archived ones
        start_time = time.time()

        msg = "[{team}/{label}] Processing done in {t}s, {count} nodes returned (from {begin} to {end})"
        self.log.info(
            msg.format(
                team=self.team_name,
                label=self.label,
                t=round(time.time() - start_time, 3),
                count=len(nodes),
                begin=list(nodes.keys())[0],
                end=list(nodes.keys())[-1],
            ))

        self.log.info(
            "[{team}/{label}] Computing the QOS for {count} nodes...".format(
                team=self.team_name, label=self.label, count=len(nodes)))

        start_time = time.time()
        QOS = {}
        metrics = []
        nodes_without_qos = []
        idx = 0

        for node, deps in nodes.items():
            self.log.info(
                "[{team}/{label}] Fetching the QOS of {count} dependencies for {node}..."
                .format(team=self.team_name,
                        label=self.label,
                        count=len(deps),
                        node=node))

            node_deps = []
            for d in deps:
                dep_name = d["name"]
                dep_label = d["label"]

                # The label contains the topic but not the redis key
                dep = "{0}.{1}".format(dep_label.split("_")[1], dep_name)

                # It's the first time we see this dependency
                if dep not in QOS.keys():

                    # We retrieve its QOS in Redis
                    qos = redis.get("{ds}.{team}.{dep}.node".format(
                        ds=ds, team=self.team_name, dep=dep))
                    if qos:
                        QOS[dep] = json.loads(qos.decode("utf-8"),
                                              cls=BoolsDpsDecoder)

                # Add the result of the dependencies for this node
                try:
                    node_deps.append(QOS[dep])
                except KeyError:
                    msg = ("The QOS of {dep} is not available "
                           "(no data in any metric ?)".format(dep=dep_name))
                    logger.warning(msg)

            if node_deps:
                msg = (
                    "[{team}/{label}] Computing the QOS of {node} using a {type} "
                    "between {count} dependencies with valid QOS...")
                self.log.info(
                    msg.format(
                        team=self.team_name,
                        label=self.label,
                        node=node,
                        type=self.type,
                        count=len(node_deps),
                    ))

                node_qos = self.compute_node_qos(data=node_deps,
                                                 start=start,
                                                 end=end)

                self.log.info("[{0}/{1}] The QOS of {2} is {3}%".format(
                    self.team_name, self.label, node, node_qos["qos"]))

                metrics.append(
                    self.format_metric(
                        metric="depc.qos.node",
                        ts=start,
                        value=node_qos["qos"],
                        tags={
                            "label": self.label,
                            "name": node,
                            "team": self.team_id
                        },
                    ))

                key = "{ds}.{team}.{label}".format(ds=ds,
                                                   team=self.team_name,
                                                   label=self.label)

                if not self.excluded_from_label_average(
                        self.team_name, self.label, node):
                    redis.zadd("{}.sorted".format(key), node, node_qos["qos"])

                # Save information to reuse it later (`bools_dps` is used in
                # OperationOperator and `qos` is used in AggregationOperator)
                redis.set("{}.{}.node".format(key, node), json.dumps(node_qos))
            else:
                self.log.warning(
                    "[{team}/{label}] {node} has no dependency with QOS".
                    format(team=self.team_name, label=self.label, node=node))
                nodes_without_qos.append(node)

                # Add it in redis to compute some stats in AfterSubdagOperator
                redis.sadd(
                    "{ds}.{team}.{label}.noqos".format(ds=ds,
                                                       team=self.team_name,
                                                       label=self.label),
                    node,
                )

            idx += 1
            if idx and idx % 1000 == 0:
                self.log.info(
                    "[{team}/{label}] {count} nodes processed in {time}s".
                    format(
                        team=self.team_name,
                        label=self.label,
                        count=idx,
                        time=round(time.time() - start_time, 3),
                    ))

        self.log.info(
            "[{team}/{label}] The QOS of {count} nodes has been computed in {time}s"
            .format(
                team=self.team_name,
                label=self.label,
                count=len(metrics),
                time=round(time.time() - start_time, 3),
            ))

        if nodes_without_qos:
            msg = "[{team}/{label}] The QOS could not be found for {count} nodes ({excerpt}, ...)"
            self.log.warning(
                msg.format(
                    team=self.team_name,
                    label=self.label,
                    count=len(nodes_without_qos),
                    excerpt=", ".join(nodes_without_qos[:5]),
                ))

        # Write metrics for Beamium
        if not metrics:
            self.log.warning(
                "[{team}/{label}] No QOS to save, chunk is finished.".format(
                    team=self.team_name, label=self.label))
        else:
            self.write_metrics(metrics)
Пример #7
0
    def execute(self, context):
        from depc.extensions import redis_scheduler as redis
        from depc.utils import get_start_end_ts

        ds = context["ds"]
        start, end = get_start_end_ts(ds)

        # Get the start_time created in BeforeSubdagOperator
        data = context["task_instance"].xcom_pull(
            task_ids="{0}.before_subdag".format(self.label)
        )

        # Save the time beween the beginning and the end of the subdag
        time_ellapsed = time.time() - data["start_time"]
        self.logger.info(
            "[{team}/{label}] Subdag done in {time} seconds".format(
                team=self.team_name, label=self.label, time=time_ellapsed
            )
        )
        self.write_metric(
            metric="depc.qos.stats",
            ts=start,
            value=time_ellapsed,
            tags={"team": self.team_id, "label": self.label, "type": "time"},
        )

        # Count the nodes without a computed QOS
        noqos_count = redis.scard(
            "{ds}.{team}.{label}.noqos".format(
                ds=ds, team=self.team_name, label=self.label
            )
        )
        self.logger.info(
            "[{team}/{label}] {count} nodes do not have associated QOS".format(
                team=self.team_name, label=self.label, count=noqos_count
            )
        )
        self.write_metric(
            metric="depc.qos.stats",
            ts=start,
            value=noqos_count,
            tags={"team": self.team_id, "label": self.label, "type": "noqos"},
        )

        # Count the nodes with a QOS
        qos_count = data["count"] - noqos_count
        self.logger.info(
            "[{team}/{label}] {count} nodes have a valid QOS".format(
                team=self.team_name, label=self.label, count=qos_count
            )
        )
        self.write_metric(
            metric="depc.qos.stats",
            ts=start,
            value=qos_count,
            tags={"team": self.team_id, "label": self.label, "type": "qos"},
        )

        # Give some nodes without QOS
        if noqos_count:
            noqos_nodes = redis.srandmember(
                "{ds}.{team}.{label}.noqos".format(
                    ds=ds, team=self.team_name, label=self.label
                ),
                10,
            )

            # TODO : we must save it somewhere in order to provide the data to the user
            self.logger.info(
                "[{team}/{label}] Examples of nodes without QOS : {nodes}".format(
                    team=self.team_name, label=self.label, nodes=str(noqos_nodes)
                )
            )