qtopology-extras v0.2.1

QTopology extras

This repository contains analytics extensions to qtopology using QMiner.

These extensions are written in Typescript.

Installation

npm install qtopology-extras

Intro

This repository contains the following extensions:

• Bolts that perform streaming operations such as windowing.
• Bolts performing anomaly detection.
• Spouts that connect to Kafka topics.
• Bolts that publish to Kafka topics.

Common data formats

GDR data

General Data Record contains timestamp, tags (simple string values) and values (simple numerics). Optionally, one can attach extra_data (arbitrary objects).

{
    "ts": "2018-09-29T12:34:56",
    "tags": { "tag1": "a", "tag2": "b" },
    "values": { "avg": 123.456 },
    "extra_data": {
        "additional": [1, 2, 3],
        "version": {
            "major": 2,
            "minor": 1,
            "release_on": "2018-09-27"
        }
    }
}

Time-series data

Time-series contains numeric value and timestamp in ISO format

{
    "ts": "2018-09-29T12:34:56",
    "val": 83.21
}

However, internally we often use numeric version of time (Unix timestamp):

{
    "ts": 1538224496000,
    "val": 83.21
}

Events

Event contains name and timestamp

{
    "ts": "2018-09-29T12:34:56",
    "name": "some_name"
}

Event windows:

{
    "ts_start": "2018-09-29T12:34:56",
    "ts_end": "2018-09-29T12:44:56",
    "names": {
        "a": 12,
        "b": 5,
        "c": 89
    },
    "vec_len_one_hot": 1.732,
    "vec_len": 89.9444
}

Alerts

Alert is written as a GDR record. It contains timestamp, alert type, source of alerts, tags of input data and extra data that describes the alert. It contains two standard tags - $alert-type and $alert-source.

{
    "ts": "2018-09-29T12:34:56",
    "tags": {
        "$alert-type": "quantile",
        "$alert-source": "bucket1.quantile",
        "tag1": "a",
        "tag2": "b"
    },
    "values": {
        "value": 1234,
        "cdf": 0.9921,
        "threshold_cdf":  0.99,
        "threshold_value":  1218
    },
    "extra_data": {}
}

Anomaly detectors

Quantile estimation

This anomaly detector uses quantile estimation to detect anomalies.

It uses name and value field queries. Name is used for separating values into buckets. Each bucket is being tracked separately.

{
    "name": "bolt_ad",
    "working_dir": "qtopology-extras",
    "type": "module_method",
    "cmd": "createBolts",
    "subtype": "quantile_ad",
    "inputs": [{ "source": "bolt_input" }],
    "init": {
        "min_count": 1000,
        "threshold_low": 0.005,
        "threshold_high": 0.995,
        "name_field": "tags.name",
        "value_field": "values.avg"
    }
}

Example input:

{
    "ts": "2018-09-29T12:34:56",
    "tags": { "tag1": "a", "tag2": "b" },
    "values": { "avg": 123.456 }
}

Example output contains same tags:

{
    "ts": "2018-09-29T12:34:56",
    "tags": {
        "$alert-type": "quantile",
        "$alert-source": "bucket1.quantile",
        "tag1": "a",
        "tag2": "b"
    },
    "values": {
        "value": 1234,
        "cdf": 0.9921,
        "threshold_cdf":  0.99,
        "threshold_value":  1218
    },
    "extra_data": {}
}

Z-score anomaly detection

This anomaly detector uses z-score to detect anomalies:

{
    "name": "bolt_ad2",
    "working_dir": "qtopology-extras",
    "type": "module_method",
    "cmd": "createBolts",
    "subtype": "zscore_ad",
    "inputs": [{ "source": "bolt_input" }],
    "init": {
        "min_count": 1000,
        "threshold_z_pos": 3,
        "threshold_z_neg": -5,
        "name_field": "tags.name",
        "value_field": "values.avg"
    }
}

Windowing operation

This bolt receives event stream and emits window statistics in regular time intervals:

{
    "name": "bolt_processing_ew",
    "working_dir": "qtopology-extras",
    "type": "module_method",
    "cmd": "createBolts",
    "subtype": "event_window",
    "inputs": [{ "source": "input" }],
    "init": {
        "window_len": 1800000,
        "step": 600000,
        "name_field": "path.to.name",
        "ts_field": "path.to.ts",
    }
}

This example emits statistics for 30-minute sliding windows, every 10 minutes.

Example input:

{
    "ts": "2018-09-29T12:34:56",
    "name": "some_name"
}

Example output contains same tags:

{
    "ts_start": "2018-09-29T12:20:00",
    "ts_end": "2018-09-29T12:30:00",
    "names": {
        "some_name": 2,
        "some_name2": 1,
        "some_name3": 1
    }
}

Utilites

Resampler

TODO

Regularizator

TODO

Tag concatenation

This bolt concatenates all tags from input GDR record into new tag. Tag names are sorted:

{
    "name": "bolt_concat_tags",
    "working_dir": "qtopology-extras",
    "type": "module_method",
    "cmd": "createBolts",
    "subtype": "concat_tags",
    "inputs": [{ "source": "input" }],
    "init": {
        "new_tag_name": "name_of_new_tag"
    }
}

Example input

{
    "ts": "2018-09-29T12:20:00",
    "tags": {
        "some_name": "abc",
        "some_name2": 112
    },
    "values": { "v1": 56 }
}

Result

{
    "ts": "2018-09-29T12:20:00",
    "tags": {
        "some_name": "abc",
        "some_name2": 112,
        "name_of_new_tag": "some_name=aabc.some_name2=112"
    },
    "values": { "v1": 56 }
}

Testing locally

Testing can be done via docker

docker build .