- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
Testing sources and sinks
If you want to check whether a job can run successfully or whether the logic is correct, you can use connectors specially designed for testing. This saves you the need to deploy external systems and can reduce interferences.
Versions
Flink Version | Description |
1.11 | Supported |
1.13 | Supported |
1.14 | Supported |
1.16 | Supported |
Datagen source
Datagen is a random data generator built into Flink. It can be used directly as a data source. For details, see the Flink document.
Below is an example of a Datagen source. It generates two fields:
id and name. id is a random number, and name is a random string.Defining a table in DDL
CREATE TABLE datagen_source_table (id INT,name STRING) WITH ('connector' = 'datagen','rows-per-second'='1' -- The number of data records generated per second.);
WITH parameters
Option | Required | Default Value | Data Type | Description |
connector | Yes | - | String | The connector to use. Here, it should be datagen. |
rows-per-second | No | 10000 | Long | The number of rows generated per second. This determines the data send rate. |
fields.#.kind | No | random | String | The value generator for the # field. Valid values include sequence and random. |
fields.#.min | No | (Minimum value of type) | (Type of field) | The minimum value the random generator can generate. This is used for numeric data types. |
fields.#.max | No | (Maximum value of type) | (Type of field) | The maximum value the random generator can generate. This is used for numeric data types. |
fields.#.length | No | 100 | Integer | The length of strings generated by the random generator. This is used for data types including char, varchar, and string. |
fields.#.start | No | - | (Type of field) | The start value of the sequence generator. |
fields.#.end | No | - | (Type of field) | The end value of the sequence generator. |
Logger sink
The Logger sink is a custom logger example provided by Stream Compute Service. It can write final data to the log file of TaskManager so that you can view the log output via Flink UI or the logging section of the Stream Compute Service console.
1. To use the Logger sink, download the JAR package. If you want to customize the output logic, you can modify the package and rebuild it.
2. Upload the package to the Stream Compute Service console. For details, see Managing Dependencies.
3. In your SQL job, reference the package.
Defining a table in DDL
CREATE TABLE logger_sink_table (id INT,name STRING) WITH ('connector' = 'logger','print-identifier' = 'DebugData');
WITH parameters
Option | Required | Data Type | Description |
connector | Yes | String | The connector to use. Here, it should be logger. |
print-identifier | No | String | The prefix for log printing. |
all-changelog-mode | No | Boolean | If you enable this, -U data will not be filtered out. This allows you to simulate ClickHouse Collapsing data streams. |
records-per-second | No | Integer | The number of records output per second. You can use this to achieve throttling. |
mute-output | No | Boolean | Whether to drop all output data and only calculate the number of records (an enhanced version of a BlackHole sink). |
Monitoring metrics
Stream Compute Service offers a series of handy metrics for the Logger sink. Click the Logger sink operator in the execution graph in Flink UI and search for one of the metrics:
numberOfInsertRecords: The number of output +I messages.
numberOfDeleteRecords: The number of output -D messages.
numberOfUpdateBeforeRecords: The number of output -U messages.
numberOfUpdateAfterRecords: The number of output +U messages.
Print sink (not recommended)
Flink is built in with the standard-output Print sink. However, because the printing format does not comply with the rules of Stream Compute Service's log collector, the data is not well displayed in the console. We recommend you use the Logger sink instead.
Defining a table in DDL
CREATE TABLE `print_table` (`id` INT,`name` STRING) WITH ('connector' = 'print');
WITH parameters
Option | Required | Default Value | Data Type | Description |
connector | Yes | - | String | The connector to use. Here, it should be print. |
print-identifier | No | - | String | The identifier (prefix) for the output data. |
standard-error | No | false | Boolean | Whether to print as standard error instead of standard output. To print as standard error, set this to True. |
Yes
No
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