Database to File

Examples of using Sling to load data from databases to storage systems

We first need to make sure our connections are available in our environment. See Environment, Storage Connections and Database Connections for more details.

Linux / Mac

export MY_SOURCE_DB='...'

$ sling conns list
+---------------+------------------+-----------------+
| CONN NAME     | CONN TYPE        | SOURCE          |
+---------------+------------------+-----------------+
| MY_S3_BUCKET  | FileSys - S3     | sling env yaml  |
| MY_SOURCE_DB  | DB - PostgreSQL  | env variable    |
| MY_GS_BUCKET  | FileSys - Google | sling env yaml  |
| MY_AZURE_CONT | FileSys - Azure  | sling env yaml  |
+---------------+------------------+-----------------+

Windows

# using windows Powershell
$env:MY_SOURCE_DB = '...'

$ sling conns list
+---------------+------------------+-----------------+
| CONN NAME     | CONN TYPE        | SOURCE          |
+---------------+------------------+-----------------+
| MY_S3_BUCKET  | FileSys - S3     | sling env yaml  |
| MY_SOURCE_DB  | DB - PostgreSQL  | env variable    |
| MY_GS_BUCKET  | FileSys - Google | sling env yaml  |
| MY_AZURE_CONT | FileSys - Azure  | sling env yaml  |
+---------------+------------------+-----------------+

Database ⇨ Local Storage (CSV)

Using CLI Flags

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_file.csv'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_csv_folder/*.csv'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_csv_folder/' \
  --tgt-options '{file_max_rows: 100000, format: csv}'

# Windows path format
$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file://C:/Temp/my_csv_folder/' \
  --tgt-options '{file_max_rows: 100000, format: csv}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: LOCAL

defaults:
  target_options:
    format: csv

streams:
  source_schema.source_table:
    object: file:///tmp/my_file.csv

  source_schema.source_table1:
    object: file:///tmp/my_csv_folder/*.csv

  source_schema.source_table2:
    object: file:///tmp/my_csv_folder/
    target_options:
      file_max_rows: 100000

  source_schema.source_table3:
    object: file://C:/Temp/my_csv_folder/ # Windows Path format
    target_options:
      file_max_rows: 100000

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/
    target_options:
      file_max_rows: 400000 # will split files into folder
  my_schema.forbidden_table:
    disabled: true

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'

# Single file export
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.csv'
        )
    }
)

# Run the replication
replication.run()

# Multiple streams with target options
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.CSV),
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.csv'
        ),
        'source_schema.source_table1': ReplicationStream(
            object='file:///tmp/my_csv_folder/*.csv'
        ),
        'source_schema.source_table2': ReplicationStream(
            object='file:///tmp/my_csv_folder/',
            target_options=TargetOptions(file_max_rows=100000)
        ),
        'source_schema.source_table3': ReplicationStream(
            object='file://C:/Temp/my_csv_folder/',  # Windows Path format
            target_options=TargetOptions(file_max_rows=100000)
        )
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

# Schema wildcard with disabled stream
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.CSV),
    streams={
        'my_schema.*': ReplicationStream(
            object='file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        )
    },
    env={'SLING_THREADS': '3'}
)

replication.run()

Database ⇨ STDOUT

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --stdout

Database ⇨ Local Storage (JSON)

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_file.json'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_json_folder/*.json'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_json_folder/' \
  --tgt-options '{file_max_bytes: 4000000, format: json}'

# Windows Path format
$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file://C:/Temp/my_json_folder/' \
  --tgt-options '{file_max_bytes: 4000000, format: json}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: LOCAL

defaults:
  target_options:
    format: json

streams:
  source_schema.source_table:
    object: file:///tmp/my_file.json

  source_schema.source_table1:
    object: file:///tmp/my_json_folder/*.json

  source_schema.source_table2:
    object: file:///tmp/my_json_folder/
    target_options:
      file_max_bytes: 4000000

  source_schema.source_table3:
    object: file://C:/Temp/my_json_folder/
    target_options:
      file_max_bytes: 4000000

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/
    target_options:
      file_max_rows: 400000 # will split files into folder
  my_schema.forbidden_table:
    disabled: true

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'

# Single JSON file export
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.json'
        )
    }
)

# Run the replication
replication.run()

# Multiple streams with target options
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.JSON),
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.json'
        ),
        'source_schema.source_table1': ReplicationStream(
            object='file:///tmp/my_json_folder/*.json'
        ),
        'source_schema.source_table2': ReplicationStream(
            object='file:///tmp/my_json_folder/',
            target_options=TargetOptions(file_max_bytes=4000000)
        ),
        'source_schema.source_table3': ReplicationStream(
            object='file://C:/Temp/my_json_folder/',  # Windows Path format
            target_options=TargetOptions(file_max_bytes=4000000)
        )
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

# Schema wildcard with disabled stream
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.JSON),
    streams={
        'my_schema.*': ReplicationStream(
            object='file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        )
    },
    env={'SLING_THREADS': '3'}
)

replication.run()

Database ⇨ Local Storage (JSON Lines)

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_file.jsonl' \
  --tgt-options '{format: jsonlines}'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_json_folder/*.jsonl'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_json_folder/' \
  --tgt-options '{file_max_bytes: 4000000, format: jsonlines}'

# Windows Path format
$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file://C:/Temp/my_json_folder/' \
  --tgt-options '{file_max_bytes: 4000000, format: jsonlines}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: LOCAL

defaults:
  target_options:
    format: jsonlines

streams:
  source_schema.source_table:
    object: file:///tmp/my_file.jsonl

  source_schema.source_table1:
    object: file:///tmp/my_jsonlines_folder/*.jsonl

  source_schema.source_table2:
    object: file:///tmp/my_jsonlines_folder/
    target_options:
      file_max_bytes: 4000000

  source_schema.source_table3:
    object: file://C:/Temp/my_jsonlines_folder/ # Windows Path format
    target_options:
      file_max_bytes: 4000000

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/
    target_options:
      file_max_rows: 400000 # will split files into folder
  my_schema.forbidden_table:
    disabled: true

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'

# Single JSON Lines file export
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.jsonl',
            target_options=TargetOptions(format=Format.JSONLINES)
        )
    }
)

# Run the replication
replication.run()

# Multiple streams with target options
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.JSONLINES),
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.jsonl'
        ),
        'source_schema.source_table1': ReplicationStream(
            object='file:///tmp/my_jsonlines_folder/*.jsonl'
        ),
        'source_schema.source_table2': ReplicationStream(
            object='file:///tmp/my_jsonlines_folder/',
            target_options=TargetOptions(file_max_bytes=4000000)
        ),
        'source_schema.source_table3': ReplicationStream(
            object='file://C:/Temp/my_jsonlines_folder/',  # Windows Path format
            target_options=TargetOptions(file_max_bytes=4000000)
        )
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

# Schema wildcard with disabled stream
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.JSONLINES),
    streams={
        'my_schema.*': ReplicationStream(
            object='file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        )
    },
    env={'SLING_THREADS': '3'}
)

replication.run()

Database ⇨ Local Storage (Parquet)

See also Incremental Examples.

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_file.parquet'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_parquet_folder/*.parquet'

$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file:///tmp/my_parquet_folder/' \
  --tgt-options '{file_max_rows: 4000000, format: parquet}'

# Windows Path format
$ sling run --src-conn MY_SOURCE_DB \
  --src-stream 'source_schema.source_table' \
  --tgt-object 'file://C:/Temp/my_parquet_folder/' \
  --tgt-options '{file_max_rows: 4000000, format: parquet}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: LOCAL

defaults:
  target_options:
    format: parquet

streams:
  source_schema.source_table:
    object: file://C:/Temp/my_file.parquet # Windows Path format

  source_schema.source_table1:
    object: file://C:/Temp/my_parquet_folder/*.parquet # Windows Path format

  source_schema.source_table2:
    object: file:///tmp/my_parquet_folder/
    target_options:
      file_max_rows: 1000000

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/
    target_options:
      file_max_rows: 400000 # will split files into folder
  my_schema.forbidden_table:
    disabled: true

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'

# Single Parquet file export
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file:///tmp/my_file.parquet'
        )
    }
)

# Run the replication
replication.run()

# Multiple streams with target options
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.PARQUET),
    streams={
        'source_schema.source_table': ReplicationStream(
            object='file://C:/Temp/my_file.parquet'  # Windows Path format
        ),
        'source_schema.source_table1': ReplicationStream(
            object='file://C:/Temp/my_parquet_folder/*.parquet'  # Windows Path format
        ),
        'source_schema.source_table2': ReplicationStream(
            object='file:///tmp/my_parquet_folder/',
            target_options=TargetOptions(file_max_rows=1000000)
        )
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

# Schema wildcard with disabled stream
replication = Replication(
    source='MY_SOURCE_DB',
    target='LOCAL',
    defaults=TargetOptions(format=Format.PARQUET),
    streams={
        'my_schema.*': ReplicationStream(
            object='file:///tmp/{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        )
    },
    env={'SLING_THREADS': '3'}
)

replication.run()

Database ⇨ Cloud Storage (CSV)

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_file.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_csv_folder/*.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_csv_folder/' --tgt-options '{file_max_rows: 100000, format: csv}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_file.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_csv_folder/*.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_csv_folder/' --tgt-options '{file_max_rows: 100000, format: csv}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_file.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_csv_folder/*.csv'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_csv_folder/' --tgt-options '{file_max_rows: 100000, format: csv}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: MY_CLOUD_STORAGE

defaults:
  object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.csv.gz
  target_options:
    format: csv
    compression: gzip

streams:

  # all tables in schema
  my_schema.*:
    object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.csv
    target_options:
      file_max_rows: 400000 # will split files into folder

  other_schema.source_table: # will use defaults

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format, Compression
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'
os.environ['MY_CLOUD_STORAGE'] = '...'

# Cloud storage export with defaults
replication = Replication(
    source='MY_SOURCE_DB',
    target='MY_CLOUD_STORAGE',
    defaults={
        'object': '{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.csv.gz',
        'target_options': TargetOptions(
            format=Format.CSV,
            compression=Compression.GZIP
        )
    },
    streams={
        # all tables in schema
        'my_schema.*': ReplicationStream(
            object='{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.csv',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'other_schema.source_table': {}  # will use defaults
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

Database ⇨ Cloud Storage (JSON)

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_file.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_json_folder/*.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: json}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_file.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_json_folder/*.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: json}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_file.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_json_folder/*.json'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: json}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: MY_CLOUD_STORAGE

defaults:
  object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.json.gz
  target_options:
    format: json
    compression: gzip

streams:

  # all tables in schema
  my_schema.*:
    object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.json
    target_options:
      file_max_rows: 400000 # will split files into folder

  other_schema.source_table: # will use defaults

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format, Compression
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'
os.environ['MY_CLOUD_STORAGE'] = '...'

# Cloud storage JSON export with defaults
replication = Replication(
    source='MY_SOURCE_DB',
    target='MY_CLOUD_STORAGE',
    defaults={
        'object': '{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.json.gz',
        'target_options': TargetOptions(
            format=Format.JSON,
            compression=Compression.GZIP
        )
    },
    streams={
        # all tables in schema
        'my_schema.*': ReplicationStream(
            object='{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.json',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'other_schema.source_table': {}  # will use defaults
    }
)

replication.run()

Database ⇨ Cloud Storage (JSON Lines)

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_file.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_json_folder/*.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: jsonlines}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_file.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_json_folder/*.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: jsonlines}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_file.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_json_folder/*.jsonl'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_json_folder/' --tgt-options '{file_max_rows: 100000, format: jsonlines}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: MY_CLOUD_STORAGE

defaults:
  object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.jsonl.gz
  target_options:
    format: jsonlines
    compression: gzip

streams:

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.jsonl
    target_options:
      file_max_rows: 400000 # will split files into folder

  my_schema.forbidden_table:
    disabled: true

  other_schema.source_table: # will use defaults

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format, Compression
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'
os.environ['MY_CLOUD_STORAGE'] = '...'

# Cloud storage JSON Lines export with defaults
replication = Replication(
    source='MY_SOURCE_DB',
    target='MY_CLOUD_STORAGE',
    defaults={
        'object': '{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.jsonl.gz',
        'target_options': TargetOptions(
            format=Format.JSONLINES,
            compression=Compression.GZIP
        )
    },
    streams={
        # all tables in schema, except "forbidden_table"
        'my_schema.*': ReplicationStream(
            object='{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.jsonl',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        ),
        'other_schema.source_table': {}  # will use defaults
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()

Database ⇨ Cloud Storage (Parquet)

See also Incremental Examples.

Using CLI Flags

sling.sh

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_file.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_parquet_folder/*.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_S3_BUCKET --tgt-object 's3://my-bucket/my_parquet_folder/' --tgt-options '{file_max_rows: 100000, format: parquet}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_file.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_parquet_folder/*.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_GS_BUCKET --tgt-object 'gs://my-bucket/my_parquet_folder/' --tgt-options '{file_max_rows: 100000, format: parquet}'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_file.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_parquet_folder/*.parquet'

$ sling run --src-conn MY_SOURCE_DB --src-stream 'source_schema.source_table' --tgt-conn MY_AZURE_CONT --tgt-object 'https://my_account.blob.core.windows.net/my-container/my_parquet_folder/' --tgt-options '{file_max_rows: 100000, format: parquet}'

---

Using Replication

Running with Sling: sling run -r /path/to/replication.yaml

replication.yaml

source: MY_SOURCE_DB
target: MY_CLOUD_STORAGE

defaults:
  object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.parquet
  target_options:
    format: parquet

streams:

  # all tables in schema, except "forbidden_table"
  my_schema.*:
    object: {stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.parquet
    target_options:
      file_max_rows: 400000 # will split files into folder
  my_schema.forbidden_table:
    disabled: true

  other_schema.source_table: # will use defaults

env:
  SLING_THREADS: 3 # run streams concurrently

---

Using Python

replication.py

from sling import Replication, ReplicationStream, TargetOptions, Format
import os

# Set environment variables
os.environ['MY_SOURCE_DB'] = '...'
os.environ['MY_CLOUD_STORAGE'] = '...'

# Cloud storage Parquet export with defaults
replication = Replication(
    source='MY_SOURCE_DB',
    target='MY_CLOUD_STORAGE',
    defaults={
        'object': '{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}.parquet',
        'target_options': TargetOptions(format=Format.PARQUET)
    },
    streams={
        # all tables in schema, except "forbidden_table"
        'my_schema.*': ReplicationStream(
            object='{stream_schema}/{stream_table}/{YYYY}_{MM}_{DD}/*.parquet',
            target_options=TargetOptions(file_max_rows=400000)
        ),
        'my_schema.forbidden_table': ReplicationStream(
            disabled=True
        ),
        'other_schema.source_table': {}  # will use defaults
    },
    env={'SLING_THREADS': '3'}  # run streams concurrently
)

replication.run()