Oracle Database Source (JDBC) Connector for Confluent Cloud¶
The fully-managed Oracle Database Source connector for Confluent Cloud can obtain a snapshot of the existing data in an Oracle database and then monitor and record all subsequent row-level changes to that data. The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data formats. All of the events for each table are recorded in a separate Apache Kafka® topic. The events can then be easily consumed by applications and services. Note that deleted records are not captured.
Note
- This Quick Start is for the fully-managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see JDBC Connector (Source and Sink) for Confluent Platform.
- If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.
Features¶
The Oracle Database Source connector provides the following features:
Topics created automatically: The connector automatically creates Kafka topics using the naming convention:
<topic.prefix><tableName>
. The tables are created with the properties:topic.creation.default.partitions=1
andtopic.creation.default.replication.factor=3
.Insert modes:
timestamp mode is enabled when only a timestamp column is specified when you enter database details.
timestamp+incrementing mode is enabled when both a timestamp column and incrementing column are specified when you enter database details.
Important
A timestamp column must not be nullable.
Database authentication: Uses password authentication.
Data formats: The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Select configuration properties:
db.timezone
poll.interval.ms
batch.max.rows
timestamp.delay.interval.ms
topic.prefix
schema.pattern
Offset management capabilities: Supports offset management. For more information, see Manage custom offsets.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Limitations¶
Be sure to review the following information.
- For connector limitations, see Oracle Database Source (JDBC) Connector limitations.
- If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
- If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.
Note
Most JSON data that uses precise decimal data represents it as a decimal number with a precision of 38 (e.g., NUMBER(38,0)
. This is too large for INT64
or FLOAT64
. INTEGER
is an alias for NUMBER(38)
and has the same issue. For this reason, this source connector uses the Connect DECIMAL type. Confluent has an article that goes into greater detail about this subject. See Kafka Connect Deep Dive – JDBC Source connector.
Manage custom offsets¶
You can manage the offsets for this connector. Offsets provide information on the point in the system from which the connector is accessing data. For more information, see Manage Offsets for Fully-Managed Connectors in Confluent Cloud.
To manage offsets:
- Manage offsets using Confluent Cloud APIs. For more information, see Cluster API reference.
To get the current offset, make a GET
request that specifies the environment, Kafka cluster, and connector name.
GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets
Host: https://api.confluent.cloud
Response:
Successful calls return HTTP 200
with a JSON payload that describes the offset.
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"protocol": "1",
"table": "{table_name}"
},
"offset": {
"incrementing": 26
}
}
],
"metadata": {
"observed_at": "2024-03-28T17:57:48.139635200Z"
}
}
Responses include the following information:
- The position of latest offset.
- The observed time of the offset in the metadata portion of the payload. The
observed_at
time indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating its offsets. Useobserved_at
to get a sense for the gap between real time and the time at which the request was made. By default, offsets are observed every minute. CallingGET
repeatedly will fetch more recently observed offsets. - Information about the connector.
- In these examples, the curly braces around “{connector_name}” indicate a replaceable value.
To update the offset, make a POST
request that specifies the environment, Kafka cluster, and connector
name. Include a JSON payload that specifies new offset and a patch type.
POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud
{
"type": "PATCH",
"offsets": [
{
"partition": {
"protocol": "1",
"table": "{table_name}"
},
"offset": {
"incrementing": 3
}
}
]
}
Considerations:
- You can only make one offset change at a time for a given connector.
- This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
- For source connectors, the connector attempts to read from the position defined by the requested offsets.
Response:
Successful calls return HTTP 202 Accepted
with a JSON payload that describes the offset.
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"protocol": "1",
"table": "{table_name}"
},
"offset": {
"incrementing": 3
}
}
],
"requested_at": "2024-03-28T17:58:45.606796307Z",
"type": "PATCH"
}
Responses include the following information:
- The requested position of the offsets in the source.
- The time of the request to update the offset.
- Information about the connector.
To delete the offset, make a POST
request that specifies the environment, Kafka cluster, and connector
name. Include a JSON payload that specifies the delete type.
POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud
{
"type": "DELETE"
}
Considerations:
- Delete requests delete the offset for the provided partition and reset to the base state. A delete request is as if you created a fresh new connector.
- This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
- Do not issue delete and patch requests at the same time.
- For source connectors, the connector attempts to read from the position defined in the base state.
Response:
Successful calls return HTTP 202 Accepted
with a JSON payload that describes the result.
{
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [],
"requested_at": "2024-03-28T17:59:45.606796307Z",
"type": "DELETE"
}
Responses include the following information:
- Empty offsets.
- The time of the request to delete the offset.
- Information about Kafka cluster and connector.
- The type of request.
To get the status of a previous offset request, make a GET
request that specifies the environment, Kafka cluster, and connector
name.
GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request/status
Host: https://api.confluent.cloud
Considerations:
- The status endpoint always shows the status of the most recent PATCH/DELETE operation.
Response:
Successful calls return HTTP 200
with a JSON payload that describes the result. The following is an example
of an applied patch.
{
"request": {
"id": "lcc-example123",
"name": "{connector_name}",
"offsets": [
{
"partition": {
"protocol": "1",
"table": "{table_name}"
},
"offset": {
"incrementing": 3
}
}
],
"requested_at": "2024-03-28T17:58:45.606796307Z",
"type": "PATCH"
},
"status": {
"phase": "APPLIED",
"message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses."
},
"previous_offsets": [
{
"partition": {
"protocol": "1",
"table": "{table_name}"
},
"offset": {
"incrementing": 26
}
}
],
"applied_at": "2024-03-28T17:58:48.079141883Z"
}
Responses include the following information:
- The original request, including the time it was made.
- The status of the request: applied, pending, or failed.
- The time you issued the status request.
- The previous offsets. These are the offsets that the connector last updated prior to updating the offsets. Use these to try to restore the state of your connector if a patch update causes your connector to fail or to return a connector to its previous state after rolling back.
JDBC modes and offsets¶
You can run the JDBC source connectors in one of four modes. Each mode uses a different offset object in its JSON payload to track the progress of the connector. The provided samples show an offset object from a JBDC source connector in incrementing mode.
bulk
- No offset. This is the default mode for JDBC source connectors.incrementing
- The offset is provided by theincrementing
property in the offset object.timestamp
- The offset is provided by thetimestamp
andtimestamp-nanos
properties in the offset object.timestamp+incrementing
- The offset is provided by theincrementing
,timestamp
andtimestamp-nanos
properties in the offset object.
JSON payload¶
The table below offers a description of the unique fields in the JSON payload for managing offsets of the JDBC Source connectors, including:
- Microsoft SQL Server Source connector
- MySQL Source connector
- Oracle Database Source connector
- PostgreSQL Source connector
Field | Definition | Required/Optional |
---|---|---|
incrementing |
Specifies the value of Available only in the following modes: incrementing, timestamp+incrementing. |
Required |
protocol |
Specifies the protocol. Available in the following modes: incrementing, timestamp, timestamp+incrementing. |
Required |
table |
The name of the table. Available in the following modes: incrementing, timestamp, timestamp+incrementing. |
Required |
timestamp |
The number of milliseconds since Available only in the following modes: timestamp, timestamp+incrementing. |
Required |
timestamp_nanos |
Fractional seconds component of the timestamp object. Available only in the following modes: timestamp, timestamp+incrementing. |
Required |
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud Oracle Database Source connector. The quick start provides the basics of selecting the connector and configuring it to obtain a snapshot of the existing data in an Oracle database and then monitoring and recording all subsequent row-level changes.
- Prerequisites
Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
The connector automatically creates Kafka topics using the naming convention:
<topic.prefix><tableName>
. The tables are created with the properties:topic.creation.default.partitions=1
andtopic.creation.default.replication.factor=3
. If you want to create topics with specific settings, create the topics before running this connector.Important
If you are configuring granular access using a service account, and you leave the optional Topic prefix (
topic.prefix
) configuration property empty, you must grant ACLCREATE
andWRITE
access to all the Kafka topics or create RBAC role bindings. To add ACLs, you use the (*) wildcard in the ACL entries as shown in the following examples.confluent kafka acl create --allow --service-account "<service-account-id>" --operation create --topic "*"
confluent kafka acl create --allow --service-account "<service-account-id>" --operation write --topic "*"
The Oracle Database System must be configured with a Pluggable Database (PDB) service name. See Configuring a Multitenant Oracle Database System for instructions for setting this up. This is used for the Database name when configuring the connection to the database.
The Oracle Database version must be 11.2.0.4 or later.
Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Make sure your connector can reach your service. Consider the following before running the connector:
- Depending on the service environment, certain network access limitations may exist. See Manage Networking for Confluent Cloud Connectors for details.
- To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors. For additional fully-managed connector networking details, see Networking and DNS.
- Do not include
jdbc:xxxx://
in the connection hostname property. An example of a connection hostname property isdatabase.example.endpoint.com
. For example,mydatabase.abc123ecs2.us-west.rds.amazonaws.com
. - Clients from Azure Virtual Networks are not allowed to access the server by default. Check that your Azure Virtual Network is correctly configured and that Allow access to Azure Services is enabled.
- See your specific cloud platform documentation for how to configure security rules for your VPC.
- Kafka cluster credentials. The following lists the different ways you can provide credentials.
- Enter an existing service account resource ID.
- Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
- Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.
Using the Confluent Cloud Console¶
Step 1: Launch your Confluent Cloud cluster¶
See the Quick Start for Confluent Cloud for installation instructions.
Step 2: Add a connector¶
In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.
Step 4: Enter the connector details¶
Note
- Make sure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
At the Oracle Database Source Connector screen, complete the following:
In the Topic prefix field, define a topic prefix your connector will
use to publish to Kafka topics. The connector will Kafka topics using the
following naming convention: <topic.prefix><tableName>
.
Important
If you are configuring granular access using a service account, and you leave the optional Topic prefix
(topic.prefix
) configuration property empty, you must grant ACL
CREATE
and WRITE
access to all the Kafka topics or create RBAC
role bindings. To add ACLs, you use the (*)
wildcard in the ACL entries as shown in the following examples.
confluent kafka acl create --allow --service-account
"<service-account-id>" --operation create --topic "*"
confluent kafka acl create --allow --service-account
"<service-account-id>" --operation write --topic "*"
- Select the way you want to provide Kafka Cluster credentials. You can
choose one of the following options:
- My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.
- Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.
- Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.
- Click Continue.
- Add the following database connection details:
- Connection host: The JDBC connection host. Do not include
jdbc:xxxx://
in the connection hostname property. An example of a connection hostname property isdatabase-1.123abc456ecs2.us-west-2.rds.amazonaws.com
. Depending on the service environment, certain network access limitations may exist. For details, see Manage Networking for Confluent Cloud Connectors. - Connection port: JDBC connection port for Oracle Database.
- Connection user: JDBC connection user for Oracle Database.
- Connection password: JDBC connection password Oracle Database.
- Database name: JDBC database name for Oracle Database.
- SSL mode: The SSL mode to use to connect to your database.
- Trust store: Upload the trust store file that contains the Certificate Authority (CA) CA information.
- Distinguished name (DN) of the database server: Use this
parameter to specify the distinguished name (DN) of the database
server. Only required if using
verify-full
SSL mode. - Trust store password: The trust store password containing server
CA certificate. Only required if using
verify-ca
orverify-full
SSL mode.
- Connection host: The JDBC connection host. Do not include
- Click Continue.
Configure the following:
- Table names: List of tables to include in copying. Use a comma-separated list to specify multiple tables.
- Select the output record value format (data going to the Kafka topic): AVRO, JSON, JSON_SR (JSON Schema), or PROTOBUF. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). For additional information, see Schema Registry Enabled Environments.
- Table types: By default, the JDBC connector will only detect
tables with type
TABLE
from the source database. This config allows a command separated list of table types to extract. - Database timezone: Name of the JDBC timezone used in the
connector when querying with time-based criteria. Defaults to
UTC
.
Show advanced configurations
Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.
Timestamp column name: Comma-separated list of one or more timestamp columns to detect new or modified rows using the COALESCE SQL function. Rows whose first non-null timestamp value is greater than the largest previous timestamp value seen will be discovered with each poll. At least one column should not be nullable.
Mode: The mode for updating a table each time it is polled. Defaults to
bulk
mode.Transaction Isolation Level: Isolation level determines how transaction integrity is visible to other users and systems.
DEFAULT
is the default isolation level configured at the database server.READ_UNCOMMITTED
is the lowest isolation level. At this level, a transaction may see changes that are not committed (that is, dirty reads) made by other transactions.READ_COMMITTED
guarantees that any data read is already committed at the moment it is read.REPEATABLE_READ
adds to the guarantees of theREAD_COMMITTED
level with the addition of also guaranteeing that any data read cannot change, if the transaction reads the same data again. However, phantom reads are possible.SERIALIZABLE
is the highest isolation level. In addition to everythingREPEATABLE_READ
guarantees,SERIALIZABLE
also eliminates phantom reads.Incrementing column name: The name of the strictly incrementing column to use to detect new rows. Any empty value indicates the column should be autodetected by looking for an auto-incrementing column. This column may not be nullable.
Quote SQL Identifiers: When to quote table names, column names, and other identifiers in SQL statements. For backward compatibility, the default value is
ALWAYS
.Numeric Mapping: Map NUMERIC values by precision and optionally scale to integral or decimal types.
Initial timestamp: The epoch timestamp used for initial queries that use timestamp criteria. The value -1 sets the initial timestamp to the current time. If not specified, the connector retrieves all data. Once the connector has managed to successfully record a source offset, this property has no effect even if changed to a different value later on.
Schema pattern: Schema pattern to fetch table metadata from the database.
Timestamp granularity for timestamp columns: Defines the granularity of the Timestamp column.
CONNECT_LOGICAL
(default) represents timestamp values using Connect’s built-in representations.NANOS_LONG
represents timestamp values as nanoseconds (ns) since the epoch (UNIX epoch time).NANOS_STRING
represents timestamp values as ns since the epoch in string format.NANOS_ISO_DATETIME_STRING
represents timestamp values in ISO formatyyyy-MM-dd'T'HH:mm:ss.n
.Poll interval (ms): Enter the number of milliseconds (ms) the connector should wait during each iteration for new change events to appear. Defaults to
1000
ms (1 second).Max rows per batch: The maximum number of rows to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.
Delay interval (ms): The amount of time to wait after a row with a certain timestamp appears before we include it in the result. You may choose to add some delay to allow transactions with an earlier timestamp to complete.
Transforms and Predicates: For details, see the Single Message Transforms (SMT) documentation.
For all property values and definitions, see Configuration Properties.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
- To change the number of tasks, use the Range Slider to select the desired number of tasks.
- Click Continue.
Verify the connection details by previewing the running configuration.
Tip
For information about previewing your connector output, see Data Previews for Confluent Cloud Connectors.
After you’ve validated that the properties are configured to your satisfaction, click Launch.
The status for the connector should go from Provisioning to Running.
Step 5: Check the Kafka topic¶
After the connector is running, verify that messages are populating your Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Using the Confluent CLI¶
Complete the following steps to set up and run the connector using the Confluent CLI.
Note
Make sure you have all your prerequisites completed.
Step 1: List the available connectors¶
Enter the following command to list available connectors:
confluent connect plugin list
Step 2: List the connector configuration properties¶
Enter the following command to show the connector configuration properties:
confluent connect plugin describe <connector-plugin-name>
The command output shows the required and optional configuration properties.
Step 3: Create the connector configuration file¶
Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.
{
"name" : "OracleDatabaseSource_0",
"connector.class": "OracleDatabaseSource",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key>",
"kafka.api.secret" : "<my-kafka-api-secret>",
"topic.prefix" : "oracle_",
"connection.host" : "<my-database-endpoint>",
"connection.port" : "1521",
"connection.user" : "<database-username>",
"connection.password": "<database-password>",
"db.name": "db078_pdb1.subnet.vcn.oraclevcn.com",
"table.whitelist": "PASSENGERS",
"timestamp.column.name": "created_at",
"output.data.format": "JSON",
"db.timezone": "UCT",
"tasks.max" : "1"
}
Note the following property definitions:
"name"
: Sets a name for your new connector."connector.class"
: Identifies the connector plugin name.
"kafka.auth.mode"
: Identifies the connector authentication mode you want to use. There are two options:SERVICE_ACCOUNT
orKAFKA_API_KEY
(the default). To use an API key and secret, specify the configuration propertieskafka.api.key
andkafka.api.secret
, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.service.account.id=<service-account-resource-ID>
. To list the available service account resource IDs, use the following command:confluent iam service-account list
For example:
confluent iam service-account list Id | Resource ID | Name | Description +---------+-------------+-------------------+------------------- 123456 | sa-l1r23m | sa-1 | Service account 1 789101 | sa-l4d56p | sa-2 | Service account 2
"topic.prefix"
: Enter a topic prefix. The connector automatically creates Kafka topics using the naming convention:<topic.prefix><tableName>
. The tables are created with the properties:topic.creation.default.partitions=1
andtopic.creation.default.replication.factor=3
. If you want to create topics with specific settings, create the topics before running this connector. If you are configuring granular access using a service account, you must set up ACLs for the topic prefix.Important
If you are configuring granular access using a service account, and you leave the optional Topic prefix (
topic.prefix
) configuration property empty, you must grant ACLCREATE
andWRITE
access to all the Kafka topics or create RBAC role bindings. To add ACLs, you use the (*) wildcard in the ACL entries as shown in the following examples.confluent kafka acl create --allow --service-account "<service-account-id>" --operation create --topic "*"
confluent kafka acl create --allow --service-account "<service-account-id>" --operation write --topic "*"
"output.data.format"
: Sets the output Kafka record value format (data coming from the connector). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf)."db.timezone"
: Identifies the database timezone. This can be any valid database timezone. The default is UTC. For more information, see this list of database timezones.
Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.
See Configuration Properties for all properties and definitions.
Step 4: Load the properties file and create the connector¶
Enter the following command to load the configuration and start the connector:
confluent connect cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file oracle-source.json
Example output:
Created connector OracleDatabaseSource_0 lcc-ix4dl
Step 5: Check the connector status¶
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type
+-----------+-------------------------+---------+-------+
lcc-ix4dl | OracleDatabaseSource_0 | RUNNING | source
Step 6: Check the Kafka topic.¶
After the connector is running, verify that messages are populating your Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Configuring a Multitenant Oracle Database System¶
Multitenancy is a standard feature for Oracle database systems, beginning with Oracle Database version 12c. Multitenancy provides a Container Database (CDB) that houses the system information and Pluggable Databases (PDBs) that house your application data and tables.
The following example OCI DB Systems screen shows the environment configuration used in this procedure.
Use the following steps to configure an Oracle multitenant database system in the Oracle Cloud Infrastructure (OCI). Once configured, you can use the Oracle Database Source (JDBC) Connector for Confluent Cloud to connect to the database and obtain a snapshot of the existing data in the database and then monitor and record all subsequent row-level changes to that data.
- Prerequisites
- Familiarity with Oracle database systems and management tools.
- A running Oracle database on OCI. To create an Oracle database on OCI, see Creating Bare Metal and Virtual Machine DB Systems.
- Authorization to create and modify an Oracle database on OCI.
- A Console Connection configured for the database system. See Connecting to the Serial Console.
- Ports 22 and 1521 open on the database machine (for SSH and SQL*Net access). For network configuration details, see Network Setup for DB Systems.
Step 1: SSH into the database VM¶
Open a Secure Shell (SSH) terminal session on the database VM and switch to the Oracle user. Note that you pass the private key for connecting to the VM instance.
ssh opc@<public-ip-address> -i </path/to/private-key>
For example:
ssh opc@192.136.114.86 -i ~/.ssh/oracle_id_rsa
Once you are on the VM, enter the following commands to switch to the Oracle user.
sudo su
su - oracle
Example output:
[opc@host ~]$ sudo su
[root@host opc]# su - oracle
Last login: Wed Jul 29 20:00:03 UTC 2020
[oracle@host ~]$
Step 2: Get the Pluggable Database (PDB) service name¶
Get the PDB service name by checking the listener status. Enter the following command on the VM as the Oracle user:
lsnrctl status LISTENER
For example:
[oracle@host ~]$ lsnrctl status LISTENER
LSNRCTL for Linux: Version 19.0.0.0.0 - Production on 29-JUL-2020 21:41:52
Copyright (c) 1991, 2019, Oracle. All rights reserved.
Connecting to (DESCRIPTION=(ADDRESS=(PROTOCOL=TCP)(HOST=host.subnet.vcn.oraclevcn.com)(PORT=1521)))
STATUS of the LISTENER
------------------------
Alias LISTENER
Version TNSLSNR for Linux: Version 19.0.0.0.0 - Production
Start Date 29-JUL-2020 17:39:05
Uptime 0 days 4 hr. 2 min. 47 sec
Trace Level off
Security ON: Local OS Authentication
SNMP OFF
Listener Parameter File /u01/app/oracle/product/19.0.0/dbhome_1/network/admin/listener.ora
Listener Log File /u01/app/oracle/diag/tnslsnr/host/listener/alert/log.xml
Listening Endpoints Summary...
(DESCRIPTION=(ADDRESS=(PROTOCOL=tcp)(HOST=host.subnet.vcn.oraclevcn.com)(PORT=1521)))
(DESCRIPTION=(ADDRESS=(PROTOCOL=ipc)(KEY=EXTPROC1521)))
(DESCRIPTION=(ADDRESS=(PROTOCOL=tcps)(HOST=host.subnet.vcn.oraclevcn.com)(PORT=5500))(Security=(my_wallet_directory=/u01/app/oracle/admin/DB0729_iad1qn/xdb_wallet))(Presentation=HTTP)(Session=RAW))
Services Summary...
Service "DB0729XDB.subnet.vcn.oraclevcn.com" has 1 instance(s).
Instance "DB0729", status READY, has 1 handler(s) for this service...
Service "DB0729_iad1qn.subnet.vcn.oraclevcn.com" has 1 instance(s).
Instance "DB0729", status READY, has 1 handler(s) for this service...
Service "a33f59386e740c51e053c701f40af1dd.subnet.vcn.oraclevcn.com" has 1 instance(s).
Instance "DB0729", status READY, has 1 handler(s) for this service...
Service "db0729_pdb1.subnet.vcn.oraclevcn.com" has 1 instance(s).
Instance "DB0729", status READY, has 1 handler(s) for this service...
The command completed successfully
In the example output above, the PDB service name you need is shown below:
(HOST=host.subnet.vcn.oraclevcn.com)(PORT=1521)
Step 3: Create the PDB service name¶
Complete the following steps on the VM to create a new tnsnames.ora
PDB
service name entry. The new entry is used when setting up the database
connection for the Oracle Database Source (JDBC) Connector for Confluent Cloud. The entry allows the connector to
establish a connection to the Oracle database.
Exit the Oracle user account.
exit
Change to the root directory.
cd /
Find the
tnsnames.ora
entries.find . -name tnsnames.ora
For example:
[oracle@host ~]$ exit logout [root@host opc]# cd / [root@host /]# find . -name tnsnames.ora ./u01/app/oracle/product/19.0.0/dbhome_1/network/admin/samples/tnsnames.ora ./u01/app/oracle/product/19.0.0/dbhome_1/network/admin/tnsnames.ora
Change to the
network/admin
directory.cd /u01/app/oracle/product/19.0.0/dbhome_1/network/admin
Edit the
tnsnames.ora
file and add the PDB service name from the listener status output. The additional PDB service name block isDB0729_PDB1
in the example.vi tnsnames.ora
For example:
DB0729_IAD1QN = (DESCRIPTION = (ADDRESS_LIST = (ADDRESS = (PROTOCOL = TCP)(HOST = host.subnet.vcn.oraclevcn.com)(PORT = 1521)) ) (CONNECT_DATA = (SERVICE_NAME = DB0729_iad1qn.subnet.vcn.oraclevcn.com) ) ) DB0729_PDB1 = (DESCRIPTION = (ADDRESS_LIST = (ADDRESS = (PROTOCOL = TCP)(HOST = host.subnet.vcn.oraclevcn.com)(PORT = 1521)) ) (CONNECT_DATA = (SERVICE_NAME = DB0729_pdb1.subnet.vcn.oraclevcn.com) ) )
Step 4: Launch the connector¶
Complete the steps in Oracle Database Source (JDBC) Connector for Confluent Cloud. When you get to the section where you need to add the database connection details, enter the PDB service name you added in the previous step. For example:
Configuration Properties¶
Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.
How should we connect to your data?¶
name
Sets a name for your connector.
- Type: string
- Valid Values: A string at most 64 characters long
- Importance: high
Kafka Cluster credentials¶
kafka.auth.mode
Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.
- Type: string
- Default: KAFKA_API_KEY
- Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
- Importance: high
kafka.api.key
Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.
- Type: password
- Importance: high
kafka.service.account.id
The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
- Type: string
- Importance: high
kafka.api.secret
Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
- Type: password
- Importance: high
Schema Config¶
schema.context.name
Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.
- Type: string
- Default: default
- Importance: medium
How do you want to prefix table names?¶
topic.prefix
Prefix to prepend to table names to generate the name of the Apache Kafka® topic to publish data to.
- Type: string
- Importance: high
How should we connect to your database?¶
connection.host
Depending on the service environment, certain network access limitations may exist. Make sure the connector can reach your service. Do not include jdbc:xxxx:// in the connection hostname property (e.g. database-1.abc234ec2.us-west.rds.amazonaws.com).
- Type: string
- Importance: high
connection.port
JDBC connection port.
- Type: int
- Valid Values: [0,…,65535]
- Importance: high
connection.user
JDBC connection user.
- Type: string
- Importance: high
connection.password
JDBC connection password.
- Type: password
- Importance: high
db.connection.type
Select database connection using sid or service name
- Type: string
- Default: SID
- Importance: high
db.name
JDBC database name.
- Type: string
- Importance: high
ssl.mode
What SSL mode should we use to connect to your database. disabled disables SSL entirely. verify-ca uses SSL for encryption and performs authentication of the server CA. verify-ca option requires a Java truststore containing the server CA and the truststore password to be provided.
- Type: string
- Default: disabled
- Importance: high
ssl.truststorefile
The trust store containing server CA certificate. Only required if using verify-ca or verify-full ssl mode.
- Type: password
- Default: [hidden]
- Importance: low
ssl.server.cert.dn
Use this paramter to specify the distinguished name (DN) of the database server. Only required if using verify-full ssl mode.
- Type: string
- Importance: low
ssl.truststorepassword
The trust store password containing server CA certificate. Only required if using verify-ca or verify-full ssl mode.
- Type: password
- Default: [hidden]
- Importance: low
Database details¶
table.whitelist
List of tables to include in copying. Use a comma-separated list to specify multiple tables (for example: “User, Address, Email”).
- Type: list
- Importance: medium
timestamp.column.name
Comma separated list of one or more timestamp columns to detect new or modified rows using the COALESCE SQL function. Rows whose first non-null timestamp value is greater than the largest previous timestamp value seen will be discovered with each poll. At least one column should not be nullable.
- Type: list
- Importance: medium
incrementing.column.name
The name of the strictly incrementing column to use to detect new rows. Any empty value indicates the column should be autodetected by looking for an auto-incrementing column. This column may not be nullable.
- Type: string
- Default: “”
- Importance: medium
table.types
By default, the JDBC connector will only detect tables with type TABLE from the source Database. This config allows a command separated list of table types to extract.
- Type: list
- Default: TABLE
- Importance: medium
schema.pattern
Schema pattern to fetch table metadata from the database.
- Type: string
- Importance: high
db.timezone
Name of the JDBC timezone used in the connector when querying with time-based criteria. Defaults to UTC.
- Type: string
- Default: UTC
- Importance: medium
numeric.mapping
Map NUMERIC values by precision and optionally scale to integral or decimal types. Use
none
if all NUMERIC columns are to be represented by Connect’s DECIMAL logical type. Usebest_fit
if NUMERIC columns should be cast to Connect’s INT8, INT16, INT32, INT64, or FLOAT64 based upon the column’s precision and scale. Usebest_fit_eager_double
if, in addition to the properties of best_fit described above, it is desirable to always cast NUMERIC columns with scale to Connect FLOAT64 type, despite potential of loss in accuracy. Useprecision_only
to map NUMERIC columns based only on the column’s precision assuming that column’s scale is 0. Thenone
option is the default, but may lead to serialization issues with Avro since Connect’s DECIMAL type is mapped to its binary representation, andbest_fit
will often be preferred since it maps to the most appropriate primitive type.- Type: string
- Default: none
- Importance: low
timestamp.granularity
Define the granularity of the Timestamp column. CONNECT_LOGICAL (default): represents timestamp values using Kafka Connect built-in representations. NANOS_LONG: represents timestamp values as nanos since epoch. NANOS_STRING: represents timestamp values as nanos since epoch in string. NANOS_ISO_DATETIME_STRING: uses iso format
- Type: string
- Default: CONNECT_LOGICAL
- Importance: low
Mode¶
mode
The mode for updating a table each time it is polled. BULK: perform a bulk load of the entire table each time it is polled. TIMESTAMP: use a timestamp (or timestamp-like) column to detect new and modified rows. This assumes the column is updated with each write, and that values are monotonically incrementing, but not necessarily unique. INCREMENTING: use a strictly incrementing column on each table to detect only new rows. Note that this will not detect modifications or deletions of existing rows. TIMESTAMP AND INCREMENTING: use two columns, a timestamp column that detects new and modified rows and a strictly incrementing column which provides a globally unique ID for updates so each row can be assigned a unique stream offset.
- Type: string
- Default: “”
- Importance: medium
quote.sql.identifiers
When to quote table names, column names, and other identifiers in SQL statements. For backward compatibility, the default value is ALWAYS.
- Type: string
- Default: ALWAYS
- Valid Values: ALWAYS, NEVER
- Importance: medium
transaction.isolation.mode
Isolation level determines how transaction integrity is visible to other users and systems. DEFAULT: This is the default isolation level configured at the Database Server. READ_UNCOMMITTED: This is the lowest isolation level. At this level, one transaction may see dirty reads (that is, not-yet-committed changes made by other transactions). READ_COMMITTED: This level guarantees that any data read is already committed at the moment it is read. REPEATABLE_READ: In addition to the guarantees of the READ_COMMITTED level, this option also guarantees that any data read cannot change, if the transaction reads the same data again. However, phantom reads are possible. SERIALIZABLE: This is the highest isolation level. In addition to everything REPEATABLE_READ guarantees, it also eliminates phantom reads.
- Type: string
- Default: DEFAULT
- Valid Values: DEFAULT, READ_COMMITTED, READ_UNCOMMITTED, REPEATABLE_READ, SERIALIZABLE
- Importance: medium
timestamp.initial
The epoch timestamp used for initial queries that use timestamp criteria. The value -1 sets the initial timestamp to the current time. If not specified, the connector retrieves all data. Once the connector has managed to successfully record a source offset, this property has no effect even if changed to a different value later on.
- Type: long
- Valid Values: [-1,…]
- Importance: medium
Connection details¶
poll.interval.ms
Frequency in ms to poll for new data in each table.
- Type: int
- Default: 5000 (5 seconds)
- Valid Values: [100,…]
- Importance: high
batch.max.rows
Maximum number of rows to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.
- Type: int
- Default: 100
- Valid Values: [1,…,5000]
- Importance: low
timestamp.delay.interval.ms
How long to wait after a row with a certain timestamp appears before we include it in the result. You may choose to add some delay to allow transactions with an earlier timestamp to complete. The first execution will fetch all available records (starting at timestamp 0) until current time minus the delay. Every following execution will get data from the last time we fetched until current time minus the delay.
- Type: int
- Default: 0
- Valid Values: [0,…]
- Importance: high
Output messages¶
output.data.format
Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF
- Type: string
- Default: JSON
- Importance: high
Number of tasks for this connector¶
tasks.max
Maximum number of tasks for the connector.
- Type: int
- Valid Values: [1,…]
- Importance: high
Next Steps¶
For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.