# DynamicFrameWriter class
DynamicFrameWriter



##  methods
Methods
+ [\$1\$1init\$1\$1](#aws-glue-api-crawler-pyspark-extensions-dynamic-frame-writer-__init__)
+ [from\$1options](#aws-glue-api-crawler-pyspark-extensions-dynamic-frame-writer-from_options)
+ [from\$1catalog](#aws-glue-api-crawler-pyspark-extensions-dynamic-frame-writer-from_catalog)
+ [from\$1jdbc\$1conf](#aws-glue-api-crawler-pyspark-extensions-dynamic-frame-writer-from_jdbc_conf)

## \$1\$1init\$1\$1
\$1\$1init\$1\$1

**`__init__(glue_context)`**
+ `glue_context` – The [GlueContext class](aws-glue-api-crawler-pyspark-extensions-glue-context.md) to use.

## from\$1options
from\$1options

**`from_options(frame, connection_type, connection_options={}, format=None, format_options={}, transformation_ctx="")`**

Writes a `DynamicFrame` using the specified connection and format.
+ `frame` – The `DynamicFrame` to write.
+ `connection_type` – The connection type. Valid values include `s3`, `mysql`, `postgresql`, `redshift`, `sqlserver`, and `oracle`.
+ `connection_options` – Connection options, such as path and database table (optional). For a `connection_type` of `s3`, an Amazon S3 path is defined.

  ```
  connection_options = {"path": "s3://aws-glue-target/temp"}
  ```

  For JDBC connections, several properties must be defined. Note that the database name must be part of the URL. It can optionally be included in the connection options.
**Warning**  
Storing passwords in your script is not recommended. Consider using `boto3` to retrieve them from AWS Secrets Manager or the AWS Glue Data Catalog.

  ```
  connection_options = {"url": "jdbc-url/database", "user": "username", "password": passwordVariable,"dbtable": "table-name", "redshiftTmpDir": "s3-tempdir-path"} 
  ```

  The `dbtable` property is the name of the JDBC table. For JDBC data stores that support schemas within a database, specify `schema.table-name`. If a schema is not provided, then the default "public" schema is used.

  For more information, see [Connection types and options for ETL in AWS Glue for Spark](aws-glue-programming-etl-connect.md).
+ `format` – A format specification (optional). This is used for an Amazon Simple Storage Service (Amazon S3) or an AWS Glue connection that supports multiple formats. See [Data format options for inputs and outputs in AWS Glue for Spark](aws-glue-programming-etl-format.md) for the formats that are supported.
+ `format_options` – Format options for the specified format. See [Data format options for inputs and outputs in AWS Glue for Spark](aws-glue-programming-etl-format.md) for the formats that are supported.
+ `transformation_ctx` – A transformation context to use (optional).

## from\$1catalog
from\$1catalog

**`from_catalog(frame, name_space, table_name, redshift_tmp_dir="", transformation_ctx="")`**

Writes a `DynamicFrame` using the specified catalog database and table name.
+ `frame` – The `DynamicFrame` to write.
+ `name_space` – The database to use.
+ `table_name` – The `table_name` to use.
+ `redshift_tmp_dir` – An Amazon Redshift temporary directory to use (optional).
+ `transformation_ctx` – A transformation context to use (optional).
+ `additional_options` – Additional options provided to AWS Glue. 

  To write to Lake Formation governed tables, you can use these additional options:
  + `transactionId` – (String) The transaction ID at which to do the write to the Governed table. This transaction can not be already committed or aborted, or the write will fail.
  + `callDeleteObjectsOnCancel ` – (Boolean, optional) If set to `true` (default), AWS Glue automatically calls the `DeleteObjectsOnCancel` API after the object is written to Amazon S3. For more information, see [DeleteObjectsOnCancel](https://docs.aws.amazon.com/lake-formation/latest/dg/aws-lake-formation-api-transactions-api.html#aws-lake-formation-api-transactions-api-DeleteObjectsOnCancel) in the *AWS Lake Formation Developer Guide*.  
**Example: Writing to a governed table in Lake Formation**  

  ```
  txId = glueContext.start_transaction(read_only=False)
  glueContext.write_dynamic_frame.from_catalog(
      frame=dyf,
      database = db, 
      table_name = tbl, 
      transformation_ctx = "datasource0", 
      additional_options={"transactionId":txId})
  ...
  glueContext.commit_transaction(txId)
  ```

## from\$1jdbc\$1conf
from\$1jdbc\$1conf

**`from_jdbc_conf(frame, catalog_connection, connection_options={}, redshift_tmp_dir = "", transformation_ctx="")`**

Writes a `DynamicFrame` using the specified JDBC connection information.
+ `frame` – The `DynamicFrame` to write.
+ `catalog_connection` – A catalog connection to use.
+ `connection_options` – Connection options, such as path and database table (optional).
+ `redshift_tmp_dir` – An Amazon Redshift temporary directory to use (optional).
+ `transformation_ctx` – A transformation context to use (optional).

## Example for write\$1dynamic\$1frame
Example

This example writes the output locally using a `connection_type` of S3 with a POSIX path argument in `connection_options`, which allows writing to local storage.

```
glueContext.write_dynamic_frame.from_options(\
frame = dyf_splitFields,\
connection_options = {'path': '/home/glue/GlueLocalOutput/'},\
connection_type = 's3',\
format = 'json')
```