Skip to content

uuhnaut69/online-merchant-monitor

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Online merchant monitor

An example about online merchant monitor based on Kafka, Kafka Stream, Kafka Connect,KSQL

Flow

DemoChart

Prerequisites

  • Java 11+
  • Docker
  • Docker-compose

Setup

  • Start env
docker-compose up -d
  • Check health
docker-compose ps
  • Create superset user
docker exec -it superset superset fab create-admin \
               --username admin \
               --firstname Superset \
               --lastname Admin \
               --email admin@superset.com \
               --password admin
  • Migrate superset local DB to latest
docker exec -it superset superset db upgrade
  • Setup superset roles
docker exec -it superset superset init

Access Superset via http://localhost:9669

Get Started

Connect to KSQL Server

docker exec -it ksqldb-cli ksql http://ksqldb-server:8088

Create kafka connector

CREATE
SOURCE CONNECTOR `postgresql-connector`
WITH (
    'connector.class' = 'io.debezium.connector.postgresql.PostgresConnector',
    'database.hostname' = 'postgresql',
    'database.port' = '5432',
    'database.user' = 'postgres',
    'database.password' = 'postgres',
    'database.dbname' = 'postgres',
    'database.server.name' = 'postgres',
    'decimal.handling.mode' = 'string',
    'key.converter' = 'org.apache.kafka.connect.storage.StringConverter',
    'key.converter.schemas.enable' = 'false',
    'value.converter' = 'io.confluent.connect.avro.AvroConverter',
    'value.converter.schema.registry.url' = 'http://schema-registry:8081',
    'transforms' = 'unwrap,ExtractField',
    'transforms.unwrap.type' = 'io.debezium.transforms.ExtractNewRecordState',
    'transforms.ExtractField.type' = 'org.apache.kafka.connect.transforms.ExtractField$Key',
    'transforms.unwrap.delete.handling.mode' = 'none',
    'transforms.ExtractField.field' = 'id'
);

Set offset to earliest

SET 'auto.offset.reset' = 'earliest';

Create DISHES KTable

CREATE TABLE DISHES
(
    rowkey VARCHAR PRIMARY KEY
) WITH (
      KAFKA_TOPIC = 'postgres.public.dishes',
      VALUE_FORMAT = 'AVRO'
      );
Name                 : DISHES
Field         | Type
------------------------------------------------
ROWKEY        | VARCHAR(STRING)  (primary key)
ID            | BIGINT
NAME          | VARCHAR(STRING)
PRICE         | VARCHAR(STRING)
TYPE          | VARCHAR(STRING)
RESTAURANT_ID | BIGINT
------------------------------------------------

Create RESTAURANTS KTable

CREATE TABLE RESTAURANTS
(
    rowkey VARCHAR PRIMARY KEY
) WITH (
      KAFKA_TOPIC = 'postgres.public.restaurants',
      VALUE_FORMAT = 'AVRO'
      );
Name                 : RESTAURANTS
 Field  | Type
-----------------------------------------
 ROWKEY | VARCHAR(STRING)  (primary key)
 ID     | BIGINT
 NAME   | VARCHAR(STRING)
-----------------------------------------

Start Data Generator

cd datagen && ./mvnw spring-boot:run

Create ORDERSTREAMS KStream

CREATE
STREAM ORDERSTREAMS (
    rowkey VARCHAR KEY
)
WITH (
    KAFKA_TOPIC = 'orders',
    VALUE_FORMAT = 'AVRO'
);
Name                 : ORDERSTREAMS
 Field         | Type
-------------------------------------------------------------
 ROWKEY        | VARCHAR(STRING)  (key)
 RESTAURANT_ID | BIGINT
 ORDER_ID      | VARCHAR(STRING)
 LAT           | DOUBLE
 LON           | DOUBLE
 CREATED_AT    | BIGINT
 ORDER_LINES   | ARRAY<STRUCT<DISH_ID BIGINT, UNIT INTEGER>>
-------------------------------------------------------------

Flatten order streams and enrich with restaurant info (1)

create
or
replace
stream order_with_restaurant
with (KAFKA_TOPIC='order_with_restaurant', KEY_FORMAT='KAFKA', VALUE_FORMAT='AVRO', TIMESTAMP ='CREATED_AT') as
select o.RESTAURANT_ID        as RESTAURANT_ID,
       r.NAME                 as NAME,
       o.ORDER_ID             as ORDER_ID,
       o.LAT                  as LAT,
       o.LON                  as LON,
       o.CREATED_AT           as CREATED_AT,
       EXPLODE(o.ORDER_LINES) as ORDER_LINE
from ORDERSTREAMS o
         inner join RESTAURANTS r on
    cast(o.RESTAURANT_ID as STRING) = r.ROWKEY partition by o.ORDER_ID emit changes;

Enrich (1) downstream with dish info

Currently KSQLDB aggregate_functions COLLECT_SET() not support MAP, STRUCT, ARRAY types so we need convert complex column to VARCHAR/STRING

create
or
replace
stream order_with_restaurant_dish
with (KAFKA_TOPIC='order_with_restaurant_dish', KEY_FORMAT='KAFKA', VALUE_FORMAT='AVRO', TIMESTAMP ='CREATED_AT') as
select owr.RESTAURANT_ID                                                as RESTAURANT_ID,
       owr.NAME                                                         as RESTAURANT_NAME,
       owr.ORDER_ID                                                     as ORDER_ID,
       owr.LAT                                                          as LAT,
       owr.LON                                                          as LON,
       owr.CREATED_AT                                                   as CREATED_AT,
       map(
               'DISH_ID' := d.ROWKEY,
               'DISH_NAME' := d.NAME,
               'DISH_PRICE' := d.PRICE,
               'DISH_TYPE' := d.TYPE,
               'UNIT' := cast(owr.ORDER_LINE -> UNIT as VARCHAR)
           )                                                            as ORDER_LINE,
       ('DISH_ID:=' + d.ROWKEY + ',DISH_NAME:=' + d.NAME + ',DISH_PRICE:=' + d.PRICE + ',DISH_TYPE:=' + d.type +
        ',ORDER_UNIT:=' + cast(owr.ORDER_LINE -> UNIT as VARCHAR))      as ORDER_LINE_STRING,
       cast(d.PRICE as DOUBLE) * cast(owr.ORDER_LINE -> UNIT as DOUBLE) as ORDER_LINE_PRICE
from ORDER_WITH_RESTAURANT owr
         inner join DISHES d on
    cast(owr.ORDER_LINE -> DISH_ID as STRING) = d.ROWKEY partition by owr.ORDER_ID emit changes;

Aggregate orders of each dish per 30 seconds

create table dish_order_30seconds_report
    with (KAFKA_TOPIC = 'dish_order_30seconds_report', KEY_FORMAT = 'AVRO', VALUE_FORMAT = 'AVRO') as
select ORDER_LINE['DISH_ID'],
       ORDER_LINE['DISH_NAME'],
       cast(as_value(ORDER_LINE['DISH_ID']) as BIGINT) as DISH_ID,
       as_value(ORDER_LINE['DISH_NAME'])               as DISH_NAME,
       as_value(FROM_UNIXTIME(WINDOWSTART))            as WINDOW_START,
       as_value(FROM_UNIXTIME(WINDOWEND))              as WINDOW_END,
       count(1)                                        as ORDER_COUNT
from order_with_restaurant_dish window TUMBLING (SIZE 30 SECONDS)
    group by ORDER_LINE['DISH_ID'], ORDER_LINE['DISH_NAME'] emit changes;

Test:

select DISH_ID, DISH_NAME, WINDOW_START, WINDOW_END, ORDER_COUNT
from dish_order_30seconds_report emit changes
limit 5;

Result:

+---------------------------------+---------------------------------+---------------------------------+---------------------------------+---------------------------------+
|DISH_ID                          |DISH_NAME                        |WINDOW_START                     |WINDOW_END                       |ORDER_COUNT                      |
+---------------------------------+---------------------------------+---------------------------------+---------------------------------+---------------------------------+
|7                                |Roasted pork meat                |2021-04-25T13:16:00.000          |2021-04-25T13:16:30.000          |1                                |
|2                                |Grilled octopus                  |2021-04-25T13:16:00.000          |2021-04-25T13:16:30.000          |1                                |
|8                                |Seaweed soup                     |2021-04-25T13:16:00.000          |2021-04-25T13:16:30.000          |1                                |
|9                                |Sour soup                        |2021-04-25T13:16:00.000          |2021-04-25T13:16:30.000          |1                                |
|5                                |Roasted duck                     |2021-04-25T13:16:00.000          |2021-04-25T13:16:30.000          |1                                |

Create sink connector save aggregate result to Citus Data

CREATE
SINK CONNECTOR `dish_order_30seconds_report_sink`
WITH (
    'connector.class' = 'io.confluent.connect.jdbc.JdbcSinkConnector',
    'connection.url' = 'jdbc:postgresql://citus:5432/merchant',
    'connection.user' = 'merchant',
    'connection.password' = 'merchant',
    'insert.mode' = 'upsert',
    'topics' = 'dish_order_30seconds_report',
    'key.converter' = 'io.confluent.connect.avro.AvroConverter',
    'key.converter.schema.registry.url' = 'http://schema-registry:8081',
    'value.converter' = 'io.confluent.connect.avro.AvroConverter',
    'value.converter.schema.registry.url' = 'http://schema-registry:8081',
    'pk.mode' = 'record_value',
    'pk.fields' = 'DISH_ID,WINDOW_START,WINDOW_END',
    'auto.create' = true,
    'auto.evolve' = true
);

Create enriched orders KTable

create table enriched_orders
    with (KAFKA_TOPIC = 'enriched_orders', KEY_FORMAT = 'AVRO', VALUE_FORMAT = 'AVRO', TIMESTAMP = 'CREATED_AT') as
select RESTAURANT_ID,
       RESTAURANT_NAME,
       ORDER_ID,
       LAT,
       LON,
       CREATED_AT,
       as_value(RESTAURANT_ID)                          as ENRICHED_ORDER_RESTAURANT_ID,
       as_value(RESTAURANT_NAME)                        as ENRICHED_ORDER_RESTAURANT_NAME,
       as_value(ORDER_ID)                               as ENRICHED_ORDER_ID,
       as_value(LAT)                                    as ENRICED_ORDER_LAT,
       as_value(LON)                                    as ENRICED_ORDER_LON,
       as_value(CREATED_AT)                             as ENRICHED_ORDER_CREATED_DATE,
       transform(collect_set(ORDER_LINE_STRING),
                 item => SPLIT_TO_MAP(item, ',', ':=')) as ENRICHED_ORDER_LINES,
       sum(ORDER_LINE_PRICE)                            as ENRICHED_ORDER_TOTAL_PRICE
from order_with_restaurant_dish
group by RESTAURANT_ID,
         RESTAURANT_NAME,
         ORDER_ID,
         LAT,
         LON,
         CREATED_AT emit changes;

Test

select *
from enriched_orders emit changes
limit 1;

Result

+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
|RESTAURANT|RESTAURANT|ORDER_ID  |LAT       |LON       |CREATED_AT|ENRICHED_O|ENRICHED_O|ENRICHED_O|ENRICED_OR|ENRICED_OR|ENRICHED_O|ENRICHED_O|ENRICHED_O|
|_ID       |_NAME     |          |          |          |          |RDER_RESTA|RDER_RESTA|RDER_ID   |DER_LAT   |DER_LON   |RDER_CREAT|RDER_LINES|RDER_TOTAL|
|          |          |          |          |          |          |URANT_ID  |URANT_NAME|          |          |          |ED_DATE   |          |_PRICE    |
+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+----------+
|1         |RESTAURANT|d0c43512-d|16.9464080|108.732419|1619356561|1         |RESTAURANT|d0c43512-d|16.9464080|108.732419|1619356561|[{DISH_NAM|720000.0  |
|          |_A        |d7a-4768-9|3337097   |66962814  |202       |          |_A        |d7a-4768-9|3337097   |66962814  |202       |E=Roasted |          |
|          |          |028-fed917|          |          |          |          |          |028-fed917|          |          |          |pork meat,|          |
|          |          |12ba88    |          |          |          |          |          |12ba88    |          |          |          | ORDER_UNI|          |
|          |          |          |          |          |          |          |          |          |          |          |          |T=4, DISH_|          |
|          |          |          |          |          |          |          |          |          |          |          |          |PRICE=1800|          |
|          |          |          |          |          |          |          |          |          |          |          |          |00.00, DIS|          |
|          |          |          |          |          |          |          |          |          |          |          |          |H_TYPE=ROA|          |
|          |          |          |          |          |          |          |          |          |          |          |          |STED, DISH|          |
|          |          |          |          |          |          |          |          |          |          |          |          |_ID=7}]   |          |

Connect Superset to Citus

postgresql://merchant:merchant@citus:5432/merchant

About

An example about online merchant monitor based on Kafka, Kafka Stream, Kafka Connect,KSQL

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages