This topic provides the DDL syntax that is used to create a MaxCompute result table, describes the parameters in the WITH clause, and provides data type mappings and sample code.
What is MaxCompute?
MaxCompute is a fast and fully managed computing platform for large-scale data warehousing. MaxCompute can process exabytes of data. It provides solutions for storing and computing mass structured data in data warehouses and provides analytics and modeling services. For more information about MaxCompute, see What is MaxCompute?.
Prerequisites
A MaxCompute table is created. For more information about how to create a MaxCompute table, see Create tables.
Limits
Only Realtime Compute for Apache Flink that uses Ververica Runtime (VVR) 2.0.0 or later supports the MaxCompute connector.
Precautions
If you use the MaxCompute connector of a version later than vvr-3.0.4-flink-1.12, a deployment failover may occur. Therefore, we recommend that you use the MaxCompute connector of vvr-3.0.4-flink-1.12 or earlier.
Principles
- Writes data. The MaxCompute sink calls an interface in MaxCompute SDK to write data to the buffer. Then, the sink uploads data to the temporary files of MaxCompute at the specified interval or when the data size in the buffer exceeds 64 MB.
- Commits sessions. When a task creates checkpoints, the MaxCompute sink calls the Tunnel commit method to commit sessions and moves temporary files to the data directory of the MaxCompute table. Then, the MaxCompute sink modifies the metadata. Note The commit method does not provide atomicity. Therefore, the MaxCompute sink supports at-least-once delivery instead of exactly-once delivery.
DDL syntax
create table odps_sink(
id INT,
user_name VARCHAR,
content VARCHAR
) WITH (
'connector' = 'odps',
'endpoint' = '<yourEndpoint>',
'tunnelEndpoint' = '<yourTunnelEndpoint>',
'project' = '<yourProjectName>',
'tablename' = '<yourTableName>',
'accessid' = '<yourAccessKeyId>',
'accesskey' = '<yourAccessKeySecret>',
'partition' = 'ds=2018****'
);
- The sequence and data type of table fields in the DDL statement must be the same as those in the MaxCompute physical table. Otherwise, the data that is queried in the MaxCompute physical table may be null or an error is returned.
- MaxCompute automatically converts all the field names that are obtained after table creation to lowercase letters. Therefore, all the names of table fields defined in the DDL statement must be lowercase letters to ensure that the field names are the same as those of the MaxCompute physical table. If a field name that is in uppercase letters exists in the DDL statement, an error that indicates a failure to identify the field may be returned during syntax verification. For example, the following error message is returned:
org.apache.flink.table.api.ValidationException: SQL validation failed. Unknown column MobileCountryCode!
.
Parameters in the WITH clause
Parameter | Description | Required | Remarks |
---|---|---|---|
connector | The type of the result table. | Yes | Set the value to odps . |
endPoint | The endpoint of MaxCompute. | Yes | For more information, see Endpoints. |
tunnelEndpoint | The endpoint of MaxCompute Tunnel. | Yes | For more information, see Endpoints. Note
|
project | The name of the MaxCompute project. | Yes | N/A. |
tableName | The name of the table in the database. | Yes | N/A. |
accessId | The AccessKey ID that is used to access MaxCompute. | Yes | N/A. |
accessKey | The AccessKey secret that is used to access MaxCompute. | Yes | N/A. |
partition | The name of a partition. | No | This parameter is required if a partitioned table is used. Take note of the following points:
|
flushIntervalMs | The flush interval for the buffer of a writer in MaxCompute Tunnel. The MaxCompute sink inserts data into the buffer. Then, the MaxCompute sink writes the data in the buffer to the destination MaxCompute table at an interval that is specified by the flushIntervalMs parameter or when the size of the buffer data exceeds the value that is specified by the batchSize parameter. | No | Default value: 30000. Unit: milliseconds. Note This parameter can be used together with the batchSize parameter. The flush operation is triggered when the condition that is specified by the batchSize parameter or the flushIntervalMs parameter is met. |
batchSize | The flush interval for the buffer of a writer in MaxCompute Tunnel. The MaxCompute sink inserts data into the buffer. Then, the MaxCompute sink writes the data in the buffer to the destination MaxCompute table when the size of the buffer data exceeds the value that is specified by the batchSize parameter. | No | Default value: 67108864. Unit: bytes. Note
|
numFlushThreads | The number of threads that are used to flush data in the buffer of a writer in MaxCompute Tunnel. Each MaxCompute sink creates the number of threads that is specified by the numFlushThreads parameter to flush data. If the value of this parameter is greater than 1, the data in different partitions can be flushed at the same time. This improves the flush operation efficiency. | No | Default value: 1. Note Only Realtime Compute for Apache Flink that uses VVR 4.0.14 or later supports this parameter. |
dynamicPartitionLimit | The maximum number of partitions. | No | Default value: 100. A map in the memory maintains the mappings between the existing partitions to which data is written and TunnelBufferedWriter. If the map size exceeds the value of the dynamicPartitionLimit parameter, the system reports the error message Too many dynamic partitions: 100, which exceeds the size limit: 100 . |
compressAlgorithm | The compression algorithm used by MaxCompute Tunnel. | No | Valid values:
Note
|
useStreamTunnel | Specifies whether to use MaxCompute Streaming Tunnel to upload data. | No | Valid values:
Note Only Realtime Compute for Apache Flink that uses VVR 4.0.13 or later supports this parameter. For more information about how to select a MaxCompute tunnel type, see Batch Tunnel and Streaming Tunnel. |
Batch Tunnel and Streaming Tunnel
Business requirement | Batch Tunnel | Streaming Tunnel |
---|---|---|
Consistent | Compared with Streaming Tunnel, Batch Tunnel is used to write all data without duplicate data to MaxCompute tables in most cases. The at-least-once semantics is used to ensure that no data is missing. Duplicate data is generated in specific partitions only if an error occurs during checkpointing and data in a deployment is written to multiple partitions at the same time. | The at-least-once semantics is used to ensure that no data is missing. If a deployment becomes abnormal, duplicate data may be generated. |
Operation efficiency | If you use Batch Tunnel, the overall operation efficiency is lower than the overall efficiency of Streaming Tunnel because you must commit data during checkpointing and create files on the server. | You do not need to commit data during checkpointing. If you use Streaming Tunnel and set the numFlushThreads parameter to a value greater than 1, upstream data can be continuously received during the flush process. Therefore, the overall operation efficiency is higher than the overall operation efficiency of Batch Tunnel. |
Data type mappings
Data type of MaxCompute | Data type of Flink |
---|---|
TINYINT | TINYINT |
SMALLINT | SMALLINT |
INT | INT |
BIGINT | BIGINT |
FLOAT | FLOAT |
DOUBLE | DOUBLE |
BOOLEAN | BOOLEAN |
DATETIME | TIMESTAMP |
TIMESTAMP | TIMESTAMP |
VARCHAR | VARCHAR |
STRING | VARCHAR |
BINARY | VARBINARY Note Only Realtime Compute for Apache Flink that uses VVR 6.0.1 and later supports the VARBINARY data type. |
DECIMAL | DECIMAL |
Sample code
- Write data to a static partition
CREATE TEMPORARY TABLE datagen_source ( id INT, len INT, content VARCHAR ) WITH ( 'connector' = 'datagen' ); CREATE TEMPORARY TABLE odps_sink ( id INT, len INT, content VARCHAR ) WITH ( 'connector' = 'odps', 'endpoint' = '<yourEndpoint>', 'tunnelEndpoint' = '<yourTunnelEndpoint>', 'project' = '<yourProjectName>', 'tablename' = '<yourTableName>', 'accessid' = '<yourAccessKeyId>', 'accesskey' = '<yourAccessKeySecret>', 'partition' = 'ds=20180905' ); INSERT INTO odps_sink SELECT id, len, content FROM datagen_source;
- Write data to a dynamic partition
CREATE TEMPORARY TABLE datagen_source ( id INT, len INT, content VARCHAR, c TIMESTAMP ) WITH ( 'connector' = 'datagen' ); CREATE TEMPORARY TABLE odps_sink ( id INT, len INT, content VARCHAR, ds VARCHAR -- The partition key column that you use to create dynamic partitions must be explicitly specified. ) WITH ( 'connector' = 'odps', 'endpoint' = '<yourEndpoint>', 'tunnelEndpoint' = '<yourTunnelEndpoint>', 'project' = '<yourProjectName>', 'tablename' = '<yourTableName>', 'accessid' = '<yourAccessKeyId>', 'accesskey' = '<yourAccessKeySecret>', 'partition' = 'ds' -- The partition value is not provided. This means that data is written to a partition that is specified by the ds field. ); INSERT INTO odps_sink SELECT id, len, content, DATE_FORMAT(c, 'yyMMdd') as ds FROM datagen_source;