I/O Connectors in Apache Beam
SkillDev toolsGuides development and usage of I/O connectors in Apache Beam. Use when working with I/O connectors, creating new connectors, or debugging data source/sink issues.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the I/O Connectors in Apache Beam skill
What this skill tells your AI
The instructions your AI receives, as published by kilo-org/kilo-marketplace in skills/io-connectors/SKILL.md and read by ahel’s review.
Overview
I/O connectors enable reading from and writing to external data sources. Beam provides 51+ Java I/O connectors and several Python connectors.
Java I/O Connectors Location
sdks/java/io/
Available Connectors
| Category | Connectors |
|---|---|
| Cloud Storage | google-cloud-platform (BigQuery, Bigtable, Spanner, Pub/Sub, GCS), amazon-web-services2, azure, azure-cosmos |
| Databases | jdbc, mongodb, cassandra, hbase, redis, neo4j, clickhouse, influxdb, singlestore, elasticsearch |
| Messaging | kafka, pulsar, rabbitmq, amqp, jms, mqtt, solace |
| File Formats | parquet, csv, json, xml, thrift, iceberg |
| Other | snowflake, splunk, cdap, debezium, hadoop-format, kudu, solr, tika |
Testing I/O Connectors
Unit Tests
./gradlew :sdks:java:io:kafka:test
./gradlew :sdks:java:io:jdbc:test
Integration Tests
On Direct Runner
./gradlew :sdks:java:io:google-cloud-platform:integrationTest
With Custom GCP Settings
./gradlew :sdks:java:io:google-cloud-platform:integrationTest \
-PgcpProject=<project> \
-PgcpTempRoot=gs://<bucket>/path
With Explicit Pipeline Options
./gradlew :sdks:java:io:jdbc:integrationTest \
-DbeamTestPipelineOptions='["--runner=TestDirectRunner"]'
Integration Test Framework
Located at it/ directory:
it/common/- Common test utilitiesit/google-cloud-platform/- GCP-specific test infrastructureit/jdbc/- JDBC test infrastructureit/kafka/- Kafka test infrastructureit/testcontainers/- Testcontainers support
Writing Integration Tests
Basic Structure
@RunWith(JUnit4.class)
public class MyIOIT {
@Rule public TestPipeline readPipeline = TestPipeline.create();
@Rule public TestPipeline writePipeline = TestPipeline.create();
@Test
public void testWriteAndRead() {
// Write data
writePipeline.apply(Create.of(testData))
.apply(MyIO.write().to(destination));
writePipeline.run().waitUntilFinish();
// Read and verify
PCollection<String> results = readPipeline.apply(MyIO.read().from(destination));
PAssert.that(results).containsInAnyOrder(expectedData);
readPipeline.run().waitUntilFinish();
}
}
Using TestPipeline
@Rule public TestPipeline pipeline = TestPipeline.create();
TestPipeline:
- Blocks on run by default (on TestDataflowRunner)
- Has 15-minute default timeout
- Reads options from
beamTestPipelineOptionssystem property
GCP I/O Connectors
BigQuery
// Read
pipeline.apply(BigQueryIO.readTableRows().from("project:dataset.table"));
// Write
data.apply(BigQueryIO.writeTableRows()
.to("project:dataset.table")
.withSchema(schema)
.withWriteDisposition(WriteDisposition.WRITE_APPEND));
Pub/Sub
// Read
pipeline.apply(PubsubIO.readStrings().fromTopic("projects/project/topics/topic"));
// Write
data.apply(PubsubIO.writeStrings().to("projects/project/topics/topic"));
Cloud Storage (TextIO)
// Read
pipeline.apply(TextIO.read().from("gs://bucket/path/*.txt"));
// Write
data.apply(TextIO.write().to("gs://bucket/output").withSuffix(".txt"));
Kafka Connector
// Read
pipeline.apply(KafkaIO.<String, String>read()
.withBootstrapServers("localhost:9092")
.withTopic("topic")
.withKeyDeserializer(StringDeserializer.class)
.withValueDeserializer(StringDeserializer.class));
// Write
data.apply(KafkaIO.<String, String>write()
.withBootstrapServers("localhost:9092")
.withTopic("topic")
.withKeySerializer(StringSerializer.class)
.withValueSerializer(StringSerializer.class));
JDBC Connector
// Read
pipeline.apply(JdbcIO.<Row>read()
.withDataSourceConfiguration(JdbcIO.DataSourceConfiguration
.create("org.postgresql.Driver", "jdbc:postgresql://host/db"))
.withQuery("SELECT * FROM table"));
// Write
data.apply(JdbcIO.<Row>write()
.withDataSourceConfiguration(config)
.withStatement("INSERT INTO table VALUES (?, ?)"));
Python I/O Location
sdks/python/apache_beam/io/
Common Python I/Os
textio- Text filesfileio- General file operationsavroio- Avro filesparquetio- Parquet filesgcp/- GCP connectors (BigQuery, Pub/Sub, Datastore, etc.)
Cross-language I/O
Beam supports using I/O connectors from one SDK in another via the expansion service.
# Start Java expansion service
./gradlew :sdks:java:io:expansion-service:runExpansionService
Creating New Connectors
Key components:
- Source - Reads data (bounded or unbounded)
- Sink - Writes data
- Read/Write transforms - User-facing API
For more detailed information on developing new I/O connectors see the Developing new I/O connectors SKILL.
Signals
- GitHub stars
- 175
- Forks
- 159
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
io-connectors- Source
- github.com/kilo-org/kilo-marketplace