Confluent, Inc. confluentgist

## reconfiguring-buffer-size-at-runtime.java
builder
   .table("users")
   .suppress(Suppressed.untilTimeLimit(
     BufferConfig.maxBytes(myConfig.getUsersBufferSize())
   ))
   ...

## testing-your-suppressions.java
driver.pipeInput(recordFactory.create(
  /* topic */     "input",
  /* key */       "A",
  /* value */     "v1",
  /* timestamp */ 10L
));
// Stream time is now 10L

driver.pipeInput(recordFactory.create("input", "A", "v2", 11L));
// Stream time is now 11L

## metrics-app-with-alerts.java
events
  .groupByKey()
  .windowedBy(
    TimeWindows.of(Duration.ofMinutes(2).withGrace(Duration.ofMinutes(2))
  )
  .count(Materialized.as("count-metric"))
  .suppress(Suppressed.untilWindowClose(BufferConfig.unbounded()))
  .filter( _ < 4 )
  .toStream()
  .foreach( /* Send that email! */)

## use-case-alerting.java
events
  .groupByKey()
  .windowedBy(TimeWindows.of(Duration.ofMinutes(2)))
  .count(Materialized.as("count-metric"))
  .filter( _ < 4 )
  .toStream()
  .foreach( /* Send that email! */)

// graph servlet queries "count-metric"

## suppress.java
events
  .groupByKey()
  .windowedBy(TimeWindows.of(Duration.ofMinutes(2)))
  .count(Materialized.as("count-metric"))

// graph servlet queries "count-metric"

## 00_numeric.mapping_README.md

      
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                confluentgist
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              Last active
              August 30, 2022 11:44
                — forked from rmoff/00_numeric.mapping_README.md
            
              
                Kafka Connect JDBC Connector - numeric.mapping
              
          
    This is a series of gists documenting testing done with the numeric.mapping option in Kafka Connect.

Oracle
MS SQL Server
Postgres
MySQL - n/a because of #563

—@rmoff January 9, 2019

  
## gist:cfcef6393cb2e2476dec25608b9de7a9
CREATE STREAM creditcardfraud_per_user WITH (VALUE_FORMAT='AVRO', KAFKA_TOPIC='creditcardfraud_preprocessed_avro') AS SELECT Time,  V1 , V2 , V3 , V4 , V5 , V6 , V7 , V8 , V9 , V10 , V11 , V12 , V13 , V14 , V15 , V16 , V17 , V18 , V19 , V20 , V21 , V22 , V23 , V24 , V25 , V26 , V27 , V28 , Amount , Class FROM creditcardfraud_enahnced c INNER JOIN USERS u on c.userid = u.userid WHERE V1 > 5 AND V2 IS NOT NULL AND u.CITY LIKE 'Premium%';

## gist:fba5c442d047270ac63a8499066651d4
SELECT Id, IFNULL(Class, -1) FROM creditcardfraud_source;

## gist:5c4870e2af590465093fe89a9e0fa5b9
SELECT Id, MASK_LEFT(User, 2) FROM creditcardfraud_source;

## gist:375dc18cc721ef57a123df508ff64500
CREATE STREAM creditcardfraud_preprocessed_avro WITH (VALUE_FORMAT='AVRO', KAFKA_TOPIC='creditcardfraud_preprocessed_avro') AS SELECT Time,  V1 , V2 , V3 , V4 , V5 , V6 , V7 , V8 , V9 , V10 , V11 , V12 , V13 , V14 , V15 , V16 , V17 , V18 , V19 , V20 , V21 , V22 , V23 , V24 , V25 , V26 , V27 , V28 , Amount , Class FROM creditcardfraud_source WHERE Class IS NOT NULL;
	builder
	.table("users")
	.suppress(Suppressed.untilTimeLimit(
	BufferConfig.maxBytes(myConfig.getUsersBufferSize())
	))
	...
	driver.pipeInput(recordFactory.create(
	/* topic */ "input",
	/* key */ "A",
	/* value */ "v1",
	/* timestamp */ 10L
	));
	// Stream time is now 10L

	driver.pipeInput(recordFactory.create("input", "A", "v2", 11L));
	// Stream time is now 11L
	events
	.groupByKey()
	.windowedBy(
	TimeWindows.of(Duration.ofMinutes(2).withGrace(Duration.ofMinutes(2))
	)
	.count(Materialized.as("count-metric"))
	.suppress(Suppressed.untilWindowClose(BufferConfig.unbounded()))
	.filter( _ < 4 )
	.toStream()
	.foreach( /* Send that email! */)
	events
	.groupByKey()
	.windowedBy(TimeWindows.of(Duration.ofMinutes(2)))
	.count(Materialized.as("count-metric"))
	.filter( _ < 4 )
	.toStream()
	.foreach( /* Send that email! */)

	// graph servlet queries "count-metric"