wally/report.py

import os
import abc
import logging
from collections import defaultdict
from typing import Dict, Any, Iterator, Tuple, cast, List, Set, Optional, Union

import numpy
from statsmodels.tsa.stattools import adfuller

import xmlbuilder3

import wally

from . import html
from .stage import Stage, StepOrder
from .test_run_class import TestRun
from .hlstorage import ResultStorage
from .utils import b2ssize, b2ssize_10, STORAGE_ROLES, unit_conversion_coef
from .statistic import calc_norm_stat_props
from .result_classes import DataSource, TimeSeries, SuiteConfig
from .suits.io.fio import FioTest, FioJobConfig
from .suits.io.fio_job import FioJobParams
from .suits.job import JobConfig
from .data_selectors import get_aggregated, AGG_TAG, summ_sensors, find_sensors_to_2d, find_nodes_by_roles
from .report_profiles import (DefStyleProfile, DefColorProfile, StyleProfile, ColorProfile,
                              default_format, io_chart_format)
from .plot import (io_chart, plot_simple_bars, plot_hmap_from_2d, plot_lat_over_time, plot_simple_over_time,
                   plot_histo_heatmap, plot_v_over_time, plot_hist)
from .resources import ResourceNames, get_resources_usage, make_iosum, IOSummary, get_cluster_cpu_load
logger = logging.getLogger("wally")


# ----------------  CONSTS ---------------------------------------------------------------------------------------------


DEBUG = False


# ----------------  STRUCTS  -------------------------------------------------------------------------------------------


# TODO: need to be revised, have to user StatProps fields instead
class StoragePerfSummary:
    def __init__(self) -> None:
        self.direct_iops_r_max = 0  # type: int
        self.direct_iops_w_max = 0  # type: int

        # 64 used instead of 4k to faster feed caches
        self.direct_iops_w64_max = 0  # type: int

        self.rws4k_10ms = 0  # type: int
        self.rws4k_30ms = 0  # type: int
        self.rws4k_100ms = 0  # type: int
        self.bw_write_max = 0  # type: int
        self.bw_read_max = 0  # type: int

        self.bw = None  # type: float
        self.iops = None  # type: float
        self.lat = None  # type: float
        self.lat_50 = None  # type: float
        self.lat_95 = None  # type: float


# --------------  AGGREGATION AND STAT FUNCTIONS  ----------------------------------------------------------------------

LEVEL_SENSORS = {("block-io", "io_queue"), ("system-cpu", "procs_blocked"), ("system-cpu", "procs_queue")}


def is_level_sensor(sensor: str, metric: str) -> bool:
    """Returns True if sensor measure level of any kind, E.g. queue depth."""
    return (sensor, metric) in LEVEL_SENSORS


def is_delta_sensor(sensor: str, metric: str) -> bool:
    """Returns True if sensor provides deltas for cumulative value. E.g. io completed in given period"""
    return not is_level_sensor(sensor, metric)


# def get_idle_load(rstorage: ResultStorage, *args, **kwargs) -> float:
#     if 'idle' not in rstorage.storage:
#         return 0.0
#     idle_time = rstorage.storage.get('idle')
#     ssum = summ_sensors(rstorage, time_range=idle_time, *args, **kwargs)
#     return numpy.average(ssum)


#  --------------------  REPORT HELPERS --------------------------------------------------------------------------------


class HTMLBlock:
    data = None  # type: str
    js_links = []  # type: List[str]
    css_links = []  # type: List[str]
    order_attr = None  # type: Any

    def __init__(self, data: str, order_attr: Any = None) -> None:
        self.data = data
        self.order_attr = order_attr

    def __eq__(self, o: Any) -> bool:
        return o.order_attr == self.order_attr  # type: ignore

    def __lt__(self, o: Any) -> bool:
        return o.order_attr > self.order_attr  # type: ignore


class Table:
    def __init__(self, header: List[str]) -> None:
        self.header = header
        self.data = []

    def add_line(self, values: List[str]) -> None:
        self.data.append(values)

    def html(self):
        return html.table("", self.header, self.data)


class Menu1st:
    engineering = "Engineering"
    summary = "Summary"
    per_job = "Per Job"


class Menu2ndEng:
    iops_time = "IOPS(time)"
    hist = "IOPS/lat overall histogram"
    lat_time = "Lat(time)"


class Menu2ndSumm:
    io_lat_qd = "IO & Lat vs QD"
    cpu_usage_qd = "CPU usage"


menu_1st_order = [Menu1st.summary, Menu1st.engineering, Menu1st.per_job]


#  --------------------  REPORTS  --------------------------------------------------------------------------------------

class ReporterBase:
    def __init__(self, rstorage: ResultStorage, style: StyleProfile, colors: ColorProfile) -> None:
        self.style = style
        self.colors = colors
        self.rstorage = rstorage

    def plt(self, func, ds: DataSource, *args, **kwargs) -> str:
        return func(self.rstorage, self.style, self.colors, ds, *args, **kwargs)


class SuiteReporter(ReporterBase, metaclass=abc.ABCMeta):
    suite_types = set()  # type: Set[str]

    @abc.abstractmethod
    def get_divs(self, suite: SuiteConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:
        pass


class JobReporter(ReporterBase, metaclass=abc.ABCMeta):
    suite_type = set()  # type: Set[str]

    @abc.abstractmethod
    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:
        pass


# # Linearization report
# class IOPSBsize(SuiteReporter):
#     """Creates graphs, which show how IOPS and Latency depend on block size"""
#
#
# # Main performance report
# class PerformanceSummary(SuiteReporter):
#     """Aggregated summary fro storage"""

# # Node load over test time
# class NodeLoad(SuiteReporter):
#     """IOPS/latency during test"""

# # Ceph operation breakout report
# class CephClusterSummary(SuiteReporter):
#     """IOPS/latency during test"""


# Main performance report
class IOQD(SuiteReporter):
    """Creates graph, which show how IOPS and Latency depend on QD"""
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:
        ts_map = defaultdict(list)  # type: Dict[FioJobParams, List[Tuple[SuiteConfig, FioJobConfig]]]
        str_summary = {}  # type: Dict[FioJobParams, List[IOSummary]]

        for job in self.rstorage.iter_job(suite):
            fjob = cast(FioJobConfig, job)
            fjob_no_qd = cast(FioJobParams, fjob.params.copy(qd=None))
            str_summary[fjob_no_qd] = (fjob_no_qd.summary, fjob_no_qd.long_summary)
            ts_map[fjob_no_qd].append((suite, fjob))

        for tpl, suites_jobs in ts_map.items():
            if len(suites_jobs) >= self.style.min_iops_vs_qd_jobs:
                iosums = [make_iosum(self.rstorage, suite, job, self.style.hist_boxes) for suite, job in suites_jobs]
                iosums.sort(key=lambda x: x.qd)
                summary, summary_long = str_summary[tpl]

                yield Menu1st.summary, Menu2ndSumm.io_lat_qd, \
                    HTMLBlock(html.H2(html.center("IOPS, BW, Lat = func(QD). " + summary_long)))

                ds = DataSource(suite_id=suite.storage_id,
                                job_id=summary,
                                node_id=AGG_TAG,
                                sensor="fio",
                                dev=AGG_TAG,
                                metric="io_over_qd",
                                tag=io_chart_format)

                fpath = self.plt(io_chart, ds, title="", legend="IOPS/BW", iosums=iosums)
                yield Menu1st.summary, Menu2ndSumm.io_lat_qd, HTMLBlock(html.center(html.img(fpath)))


class ResourceQD(SuiteReporter):
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:
        qd_grouped_jobs = {}  # type: Dict[FioJobParams, List[FioJobConfig]]
        test_nc = len(list(find_nodes_by_roles(self.rstorage, ['testnode'])))
        for job in self.rstorage.iter_job(suite):
            fjob = cast(FioJobConfig, job)
            if fjob.bsize != 4:
                continue

            fjob_no_qd = cast(FioJobParams, fjob.params.copy(qd=None))
            qd_grouped_jobs.setdefault(fjob_no_qd, []).append(fjob)

        for jc_no_qd, jobs in sorted(qd_grouped_jobs.items()):
            cpu_usage2qd = {}
            for job in jobs:
                usage, iops_ok = get_resources_usage(suite, job, self.rstorage, hist_boxes=self.style.hist_boxes,
                                                     large_block=self.style.large_blocks)

                if iops_ok:
                    cpu_usage2qd[job.qd] = usage[ResourceNames.storage_cpu_s]

            if len(cpu_usage2qd) < StyleProfile.min_iops_vs_qd_jobs:
                continue

            labels, vals, errs = zip(*((l, avg, dev) for l, (_, avg, dev) in sorted(cpu_usage2qd.items())))

            if test_nc == 1:
                labels = list(map(str, labels))
            else:
                labels = ["{} * {}".format(label, test_nc) for label in labels]

            ds = DataSource(suite_id=suite.storage_id,
                            job_id=jc_no_qd.summary,
                            node_id="cluster",
                            sensor=AGG_TAG,
                            dev='cpu',
                            metric="cpu_for_iop",
                            tag=io_chart_format)

            fpath = self.plt(plot_simple_bars, ds, jc_no_qd.long_summary, labels, vals, errs,
                             xlabel="CPU time per IOP", ylabel="QD * Test nodes" if test_nc != 1 else "QD",
                             x_formatter=(lambda x, pos: b2ssize_10(x) + 's'),
                             one_point_zero_line=False)

            yield Menu1st.summary, Menu2ndSumm.cpu_usage_qd, HTMLBlock(html.center(html.img(fpath)))


class StatInfo(JobReporter):
    """Statistic info for job results"""
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        fjob = cast(FioJobConfig, job)
        io_sum = make_iosum(self.rstorage, suite, fjob, self.style.hist_boxes)

        caption = "Test summary - " + job.params.long_summary
        test_nc = len(list(find_nodes_by_roles(self.rstorage, ['testnode'])))
        if test_nc > 1:
            caption += " * {} nodes".format(test_nc)

        res = html.H2(html.center(caption))
        stat_data_headers = ["Name",
                             "Total done",
                             "Average ~ Dev",
                             "Conf interval",
                             "Mediana",
                             "Mode",
                             "Kurt / Skew",
                             "95%",
                             "99%",
                             "ADF test"]

        align = ['left'] + ['right'] * (len(stat_data_headers) - 1)

        bw_units = "B"
        bw_target_units = bw_units + 'ps'
        bw_coef = float(unit_conversion_coef(io_sum.bw.units, bw_target_units))

        adf_v, *_1, stats, _2 = adfuller(io_sum.bw.data)

        for v in ("1%", "5%", "10%"):
            if adf_v <= stats[v]:
                ad_test = v
                break
        else:
            ad_test = "Failed"

        bw_data = ["Bandwidth",
                   b2ssize(io_sum.bw.data.sum() * bw_coef) + bw_units,
                   "{}{} ~ {}{}".format(b2ssize(io_sum.bw.average * bw_coef), bw_target_units,
                                        b2ssize(io_sum.bw.deviation * bw_coef), bw_target_units),
                   b2ssize(io_sum.bw.confidence * bw_coef) + bw_target_units,
                   b2ssize(io_sum.bw.perc_50 * bw_coef) + bw_target_units,
                   "-",
                   "{:.2f} / {:.2f}".format(io_sum.bw.kurt, io_sum.bw.skew),
                   b2ssize(io_sum.bw.perc_5 * bw_coef) + bw_target_units,
                   b2ssize(io_sum.bw.perc_1 * bw_coef) + bw_target_units,
                   ad_test]

        stat_data = [bw_data]

        if fjob.bsize < StyleProfile.large_blocks:
            iops_coef = float(unit_conversion_coef(io_sum.bw.units, 'KiBps')) / fjob.bsize
            iops_data = ["IOPS",
                         b2ssize_10(io_sum.bw.data.sum() * iops_coef),
                         "{}IOPS ~ {}IOPS".format(b2ssize_10(io_sum.bw.average * iops_coef),
                                                  b2ssize_10(io_sum.bw.deviation * iops_coef)),
                         b2ssize_10(io_sum.bw.confidence * iops_coef) + "IOPS",
                         b2ssize_10(io_sum.bw.perc_50 * iops_coef) + "IOPS",
                         "-",
                         "{:.2f} / {:.2f}".format(io_sum.bw.kurt, io_sum.bw.skew),
                         b2ssize_10(io_sum.bw.perc_5 * iops_coef) + "IOPS",
                         b2ssize_10(io_sum.bw.perc_1 * iops_coef) + "IOPS",
                         ad_test]

            lat_target_unit = 's'
            lat_coef = unit_conversion_coef(io_sum.lat.units, lat_target_unit)
            # latency
            lat_data = ["Latency",
                        "-",
                        "-",
                        "-",
                        b2ssize_10(io_sum.lat.perc_50 * lat_coef) + lat_target_unit,
                        "-",
                        "-",
                        b2ssize_10(io_sum.lat.perc_95 * lat_coef) + lat_target_unit,
                        b2ssize_10(io_sum.lat.perc_99 * lat_coef) + lat_target_unit,
                        '-']

            # sensor usage
            stat_data.extend([iops_data, lat_data])

        res += html.center(html.table("Load stats info", stat_data_headers, stat_data, align=align))
        yield Menu1st.per_job, job.summary, HTMLBlock(res)


class Resources(JobReporter):
    """Statistic info for job results"""
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        records, iops_ok = get_resources_usage(suite, job, self.rstorage,
                                               large_block=self.style.large_blocks,
                                               hist_boxes=self.style.hist_boxes)

        table_structure = [
            "Service provided",
            (ResourceNames.io_made, ResourceNames.data_tr),
            "Test nodes total load",
            (ResourceNames.test_send_pkt, ResourceNames.test_send),
            (ResourceNames.test_recv_pkt, ResourceNames.test_recv),
            (ResourceNames.test_net_pkt, ResourceNames.test_net),
            (ResourceNames.test_write_iop, ResourceNames.test_write),
            (ResourceNames.test_read_iop, ResourceNames.test_read),
            (ResourceNames.test_iop, ResourceNames.test_rw),
            "Storage nodes resource consumed",
            (ResourceNames.storage_send_pkt, ResourceNames.storage_send),
            (ResourceNames.storage_recv_pkt, ResourceNames.storage_recv),
            (ResourceNames.storage_net_pkt, ResourceNames.storage_net),
            (ResourceNames.storage_write_iop, ResourceNames.storage_write),
            (ResourceNames.storage_read_iop, ResourceNames.storage_read),
            (ResourceNames.storage_iop, ResourceNames.storage_rw),
            (ResourceNames.storage_cpu_s, ResourceNames.storage_cpu_s_b),
        ]  # type: List[Union[str, Tuple[Optional[str], ...]]

        if not iops_ok:
            table_structure2 = []
            for line in table_structure:
                if isinstance(line, str):
                    table_structure2.append(line)
                else:
                    assert len(line) == 2
                    table_structure2.append((line[1],))
            table_structure = table_structure2

        yield Menu1st.per_job, job.summary, HTMLBlock(html.H2(html.center("Resources usage")))

        doc = xmlbuilder3.XMLBuilder("table",
                                     **{"class": "table table-bordered table-striped table-condensed table-hover",
                                        "style": "width: auto;"})

        with doc.thead:
            with doc.tr:
                [doc.th(header) for header in ["Resource", "Usage count", "To service"] * (2 if iops_ok else 1)]

        cols = 6 if iops_ok else 3
        col_per_tp = 3

        short_name = {
            name: (name if name in {ResourceNames.io_made, ResourceNames.data_tr}
                   else " ".join(name.split()[2:]).capitalize())
            for name in records.keys()
        }

        short_name[ResourceNames.storage_cpu_s] = "CPU (s/IOP)"
        short_name[ResourceNames.storage_cpu_s_b] = "CPU (s/B)"

        with doc.tbody:
            with doc.tr:
                if iops_ok:
                    doc.td(colspan=str(col_per_tp)).center.b("Operations")
                doc.td(colspan=str(col_per_tp)).center.b("Bytes")

            for line in table_structure:
                with doc.tr:
                    if isinstance(line, str):
                        with doc.td(colspan=str(cols)):
                            doc.center.b(line)
                    else:
                        for name in line:
                            if name is None:
                                doc.td("-", colspan=str(col_per_tp))
                                continue

                            amount_s, avg, dev = records[name]

                            if name in (ResourceNames.storage_cpu_s, ResourceNames.storage_cpu_s_b) and avg is not None:
                                if dev is None:
                                    rel_val_s = b2ssize_10(avg) + 's'
                                else:
                                    dev_s = str(int(dev * 100 / avg)) + "%" if avg > 1E-9 else b2ssize_10(dev) + 's'
                                    rel_val_s = "{}s ~ {}".format(b2ssize_10(avg), dev_s)
                            else:
                                if avg is None:
                                    rel_val_s = '-'
                                else:
                                    avg_s = int(avg) if avg > 10 else '{:.1f}'.format(avg)
                                    if dev is None:
                                        rel_val_s = avg_s
                                    else:
                                        if avg > 1E-5:
                                            dev_s = str(int(dev * 100 / avg)) + "%"
                                        else:
                                            dev_s = int(dev) if dev > 10 else '{:.1f}'.format(dev)
                                        rel_val_s = "{} ~ {}".format(avg_s, dev_s)

                            doc.td(short_name[name], align="left")
                            doc.td(amount_s, align="right")

                            if avg is None or avg < 0.9:
                                doc.td(rel_val_s, align="right")
                            elif avg < 2.0:
                                doc.td(align="right").font(rel_val_s, color='green')
                            elif avg < 5.0:
                                doc.td(align="right").font(rel_val_s, color='orange')
                            else:
                                doc.td(align="right").font(rel_val_s, color='red')

        res = xmlbuilder3.tostr(doc).split("\n", 1)[1]
        yield Menu1st.per_job, job.summary, HTMLBlock(html.center(res))

        iop_names = [ResourceNames.test_write_iop, ResourceNames.test_read_iop, ResourceNames.test_iop,
                     ResourceNames.storage_write_iop, ResourceNames.storage_read_iop, ResourceNames.storage_iop]

        bytes_names = [ResourceNames.test_write, ResourceNames.test_read, ResourceNames.test_rw,
                       ResourceNames.test_send, ResourceNames.test_recv, ResourceNames.test_net,
                       ResourceNames.storage_write, ResourceNames.storage_read, ResourceNames.storage_rw,
                       ResourceNames.storage_send, ResourceNames.storage_recv, ResourceNames.storage_net]

        net_pkt_names = [ResourceNames.test_send_pkt, ResourceNames.test_recv_pkt, ResourceNames.test_net_pkt,
                         ResourceNames.storage_send_pkt, ResourceNames.storage_recv_pkt, ResourceNames.storage_net_pkt]

        pairs = [("bytes", bytes_names)]
        if iops_ok:
            pairs.insert(0, ('iop', iop_names))
            pairs.append(('Net packets per IOP', net_pkt_names))

        yield Menu1st.per_job, job.summary, \
            HTMLBlock(html.H2(html.center("Resource consumption per service provided")))

        for tp, names in pairs:
            vals = []
            devs = []
            avail_names = []
            for name in names:
                if name in records:
                    avail_names.append(name)
                    _, avg, dev = records[name]

                    if dev is None:
                        dev = 0

                    vals.append(avg)
                    devs.append(dev)

            # synchronously sort values and names, values is a key
            vals, names, devs = map(list, zip(*sorted(zip(vals, names, devs))))

            ds = DataSource(suite_id=suite.storage_id,
                            job_id=job.storage_id,
                            node_id=AGG_TAG,
                            sensor='resources',
                            dev=AGG_TAG,
                            metric=tp.replace(' ', "_") + '2service_bar',
                            tag=default_format)

            fname = self.plt(plot_simple_bars, ds, tp.capitalize(),
                             [name.replace(" nodes", "") for name in names],
                             vals, devs)

            yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fname))


class BottleNeck(JobReporter):
    """Statistic info for job results"""
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        nodes = list(find_nodes_by_roles(self.rstorage, STORAGE_ROLES))

        sensor = 'block-io'
        metric = 'io_queue'
        bn_val = 16

        for node in nodes:
            bn = 0
            tot = 0
            for _, ds in self.rstorage.iter_sensors(node_id=node.node_id, sensor=sensor, metric=metric):
                if ds.dev in ('sdb', 'sdc', 'sdd', 'sde'):
                    data = self.rstorage.load_sensor(ds)
                    p1 = job.reliable_info_range_s[0] * unit_conversion_coef('s', data.time_units)
                    p2 = job.reliable_info_range_s[1] * unit_conversion_coef('s', data.time_units)
                    idx1, idx2 = numpy.searchsorted(data.times, (p1, p2))
                    bn += (data.data[idx1: idx2] > bn_val).sum()
                    tot += idx2 - idx1
            print(node, bn, tot)

        yield Menu1st.per_job, job.summary, HTMLBlock("")


# CPU load
class CPULoadPlot(JobReporter):
    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        # plot CPU time
        for rt, roles in [('storage', STORAGE_ROLES), ('test', ['testnode'])]:
            cpu_ts = get_cluster_cpu_load(self.rstorage, roles, job.reliable_info_range_s)
            tss = [(name, ts.data * 100 / cpu_ts['total'].data)
                   for name, ts in cpu_ts.items()
                   if name in {'user', 'sys', 'idle', 'iowait'}]


            ds = cpu_ts['idle'].source(job_id=job.storage_id, suite_id=suite.storage_id,
                                       node_id=AGG_TAG, metric='allcpu', tag=rt + '.plt.' + default_format)

            fname = self.plt(plot_simple_over_time, ds, tss=tss, average=True, ylabel="CPU time %",
                             title="{} nodes CPU usage".format(rt.capitalize()),
                             xlabel="Time from test begin")

            yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fname))


# IO time and QD
class QDIOTimeHeatmap(JobReporter):
    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        # TODO: fix this hardcode, need to track what devices are actually used on test and storage nodes
        # use saved storage info in nodes

        journal_devs = None
        storage_devs = None
        test_nodes_devs = ['rbd0']

        for node in find_nodes_by_roles(self.rstorage, STORAGE_ROLES):
            cjd = set(node.params['ceph_journal_devs'])
            if journal_devs is None:
                journal_devs = cjd
            else:
                assert journal_devs == cjd, "{!r} != {!r}".format(journal_devs, cjd)

            csd = set(node.params['ceph_storage_devs'])
            if storage_devs is None:
                storage_devs = csd
            else:
                assert storage_devs == csd, "{!r} != {!r}".format(storage_devs, csd)

        trange = (job.reliable_info_range[0] // 1000, job.reliable_info_range[1] // 1000)

        for name, devs, roles in [('storage', storage_devs, STORAGE_ROLES),
                                  ('journal', journal_devs, STORAGE_ROLES),
                                  ('test', test_nodes_devs, ['testnode'])]:

            yield Menu1st.per_job, job.summary, \
                HTMLBlock(html.H2(html.center("{} IO heatmaps".format(name.capitalize()))))

            # QD heatmap
            ioq2d = find_sensors_to_2d(self.rstorage, roles, sensor='block-io', devs=devs,
                                       metric='io_queue', time_range=trange)

            ds = DataSource(suite.storage_id, job.storage_id, AGG_TAG, 'block-io', name, tag="hmap." + default_format)

            fname = self.plt(plot_hmap_from_2d, ds(metric='io_queue'), data2d=ioq2d, xlabel='Time', ylabel="IO QD",
                             title=name.capitalize() + " devs QD", bins=StyleProfile.qd_bins)
            yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fname))

            # Block size heatmap
            wc2d = find_sensors_to_2d(self.rstorage, roles, sensor='block-io', devs=devs,
                                      metric='writes_completed', time_range=trange)
            wc2d[wc2d < 1E-3] = 1
            sw2d = find_sensors_to_2d(self.rstorage, roles, sensor='block-io', devs=devs,
                                      metric='sectors_written', time_range=trange)
            data2d = sw2d / wc2d / 1024
            fname = self.plt(plot_hmap_from_2d, ds(metric='wr_block_size'),
                             data2d=data2d, title=name.capitalize() + " write block size",
                             ylabel="IO bsize, KiB", xlabel='Time', bins=StyleProfile.block_size_bins)
            yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fname))

            # iotime heatmap
            wtime2d = find_sensors_to_2d(self.rstorage, roles, sensor='block-io', devs=devs,
                                         metric='io_time', time_range=trange)
            fname = self.plt(plot_hmap_from_2d, ds(metric='io_time'), data2d=wtime2d,
                             xlabel='Time', ylabel="IO time (ms) per second",
                             title=name.capitalize() + " iotime", bins=StyleProfile.iotime_bins)
            yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fname))


# IOPS/latency over test time for each job
class LoadToolResults(JobReporter):
    """IOPS/latency during test"""
    suite_types = {'fio'}

    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        fjob = cast(FioJobConfig, job)

        yield Menu1st.per_job, job.summary, HTMLBlock(html.H2(html.center("Load tool results")))

        agg_io = get_aggregated(self.rstorage, suite, fjob, "bw")
        if fjob.bsize >= DefStyleProfile.large_blocks:
            title = "Fio measured Bandwidth over time"
            units = "MiBps"
            agg_io.data //= int(unit_conversion_coef(units, agg_io.units))
        else:
            title = "Fio measured IOPS over time"
            agg_io.data //= (int(unit_conversion_coef("KiBps", agg_io.units)) * fjob.bsize)
            units = "IOPS"

        fpath = self.plt(plot_v_over_time, agg_io.source(tag='ts.' + default_format), title, units, agg_io)
        yield Menu1st.per_job, fjob.summary, HTMLBlock(html.img(fpath))

        if fjob.bsize < DefStyleProfile.large_blocks:
            agg_lat = get_aggregated(self.rstorage, suite, fjob, "lat").copy()
            TARGET_UNITS = 'ms'
            coef = unit_conversion_coef(agg_lat.units, TARGET_UNITS)
            agg_lat.histo_bins = agg_lat.histo_bins.copy() * float(coef)
            agg_lat.units = TARGET_UNITS

            fpath = self.plt(plot_lat_over_time, agg_lat.source(tag='ts.' + default_format), "Latency", agg_lat,
                             ylabel="Latency, " + agg_lat.units)
            yield Menu1st.per_job, fjob.summary, HTMLBlock(html.img(fpath))

            fpath = self.plt(plot_histo_heatmap, agg_lat.source(tag='hmap.' + default_format),
                             "Latency heatmap", agg_lat, ylabel="Latency, " + agg_lat.units, xlabel='Test time')

            yield Menu1st.per_job, fjob.summary, HTMLBlock(html.img(fpath))

        fjob = cast(FioJobConfig, job)

        agg_io = get_aggregated(self.rstorage, suite, fjob, "bw")

        if fjob.bsize >= DefStyleProfile.large_blocks:
            title = "BW distribution"
            units = "MiBps"
            agg_io.data //= int(unit_conversion_coef(units, agg_io.units))
        else:
            title = "IOPS distribution"
            agg_io.data //= (int(unit_conversion_coef("KiBps", agg_io.units)) * fjob.bsize)
            units = "IOPS"

        io_stat_prop = calc_norm_stat_props(agg_io, bins_count=StyleProfile.hist_boxes)
        fpath = self.plt(plot_hist, agg_io.source(tag='hist.' + default_format), title, units, io_stat_prop)
        yield Menu1st.per_job, fjob.summary, HTMLBlock(html.img(fpath))


# Cluster load over test time
class ClusterLoad(JobReporter):
    """IOPS/latency during test"""

    # TODO: units should came from sensor
    storage_sensors = [
        ('block-io', 'reads_completed', "Read", 'iop'),
        ('block-io', 'writes_completed', "Write", 'iop'),
        ('block-io', 'sectors_read', "Read", 'MiB'),
        ('block-io', 'sectors_written', "Write", 'MiB'),
    ]

    def get_divs(self, suite: SuiteConfig, job: JobConfig) -> Iterator[Tuple[str, str, HTMLBlock]]:

        yield Menu1st.per_job, job.summary, HTMLBlock(html.H2(html.center("Cluster load")))

        sensors = []
        max_iop = 0
        max_bytes = 0

        for sensor, metric, op, units in self.storage_sensors:
            ts = summ_sensors(self.rstorage, STORAGE_ROLES, sensor, metric, job.reliable_info_range_s)
            ds = DataSource(suite_id=suite.storage_id,
                            job_id=job.storage_id,
                            node_id="storage",
                            sensor=sensor,
                            dev=AGG_TAG,
                            metric=metric,
                            tag="ts." + default_format)

            data = ts.data if units != 'MiB' else ts.data * float(unit_conversion_coef(ts.units, 'MiB'))
            ts = TimeSeries(name="",
                            times=numpy.arange(*job.reliable_info_range_s),
                            data=data,
                            raw=None,
                            units=units if ts.units is None else ts.units,
                            time_units=ts.time_units,
                            source=ds,
                            histo_bins=ts.histo_bins)

            sensors.append(("{} {}".format(op, units), ds, ts, units))

            if units == 'iop':
                max_iop = max(max_iop, data.sum())
            else:
                assert units == 'MiB'
                max_bytes = max(max_bytes, data.sum())

        for title, ds, ts, units in sensors:
            if ts.data.sum() >= (max_iop if units == 'iop' else max_bytes) * DefStyleProfile.min_load_diff:
                fpath = self.plt(plot_v_over_time, ds, title, units, ts=ts)
                yield Menu1st.per_job, job.summary, HTMLBlock(html.img(fpath))
            else:
                logger.info("Hide '%s' plot for %s, as it's cum load is less then %s%%",
                            title, job.summary, int(DefStyleProfile.min_load_diff * 100))


# ------------------------------------------  REPORT STAGES  -----------------------------------------------------------


class HtmlReportStage(Stage):
    priority = StepOrder.REPORT

    def run(self, ctx: TestRun) -> None:
        rstorage = ResultStorage(ctx.storage)

        job_reporters_cls = [StatInfo, Resources, LoadToolResults, ClusterLoad, CPULoadPlot, QDIOTimeHeatmap]
        job_reporters = [rcls(rstorage, DefStyleProfile, DefColorProfile) for rcls in job_reporters_cls]

        suite_reporters_cls = [IOQD, ResourceQD]
        suite_reporters = [rcls(rstorage, DefStyleProfile, DefColorProfile) for rcls in suite_reporters_cls]

        root_dir = os.path.dirname(os.path.dirname(wally.__file__))
        doc_templ_path = os.path.join(root_dir, "report_templates/index.html")
        report_template = open(doc_templ_path, "rt").read()
        css_file_src = os.path.join(root_dir, "report_templates/main.css")
        css_file = open(css_file_src, "rt").read()

        menu_block = []
        content_block = []
        link_idx = 0

        # matplotlib.rcParams.update(ctx.config.reporting.matplotlib_params.raw())
        # ColorProfile.__dict__.update(ctx.config.reporting.colors.raw())
        # StyleProfile.__dict__.update(ctx.config.reporting.style.raw())

        items = defaultdict(lambda: defaultdict(list))  # type: Dict[str, Dict[str, List[HTMLBlock]]]
        DEBUG = False
        job_summ_sort_order = []

        # TODO: filter reporters
        for suite in rstorage.iter_suite(FioTest.name):
            all_jobs = list(rstorage.iter_job(suite))
            all_jobs.sort(key=lambda job: job.params)

            new_jobs_in_order = [job.summary for job in all_jobs]
            same = set(new_jobs_in_order).intersection(set(job_summ_sort_order))
            assert not same, "Job with same names in different suits found: " + ",".join(same)
            job_summ_sort_order.extend(new_jobs_in_order)

            for job in all_jobs[:1]:
                try:
                    for reporter in job_reporters:
                        logger.debug("Start reporter %s on job %s suite %s",
                                     reporter.__class__.__name__, job.summary, suite.test_type)
                        for block, item, html in reporter.get_divs(suite, job):
                            items[block][item].append(html)
                    if DEBUG:
                        break
                except Exception:
                    logger.exception("Failed to generate report for %s", job.summary)

            for reporter in suite_reporters:
                try:
                    logger.debug("Start reporter %s on suite %s", reporter.__class__.__name__, suite.test_type)
                    for block, item, html in reporter.get_divs(suite):
                        items[block][item].append(html)
                except Exception as exc:
                    logger.exception("Failed to generate report")

            if DEBUG:
                break

        logger.debug("Generating result html")

        for idx_1st, menu_1st in enumerate(sorted(items, key=lambda x: menu_1st_order.index(x))):
            menu_block.append(
                '<a href="#item{}" class="nav-group" data-toggle="collapse" data-parent="#MainMenu">{}</a>'
                .format(idx_1st, menu_1st)
            )
            menu_block.append('<div class="collapse" id="item{}">'.format(idx_1st))

            if menu_1st == Menu1st.per_job:
                in_order = sorted(items[menu_1st], key=job_summ_sort_order.index)
            else:
                in_order = sorted(items[menu_1st])

            for menu_2nd in in_order:
                menu_block.append('    <a href="#content{}" class="nav-group-item">{}</a>'
                                  .format(link_idx, menu_2nd))
                content_block.append('<div id="content{}">'.format(link_idx))
                content_block.extend("    " + x.data for x in items[menu_1st][menu_2nd])
                content_block.append('</div>')
                link_idx += 1
            menu_block.append('</div>')

        report = report_template.replace("{{{menu}}}", ("\n" + " " * 16).join(menu_block))
        report = report.replace("{{{content}}}", ("\n" + " " * 16).join(content_block))
        report_path = rstorage.put_report(report, "index.html")
        rstorage.put_report(css_file, "main.css")
        logger.info("Report is stored into %r", report_path)