Snowflake

target-snowflake (transferwise variant)

Snowflake database loader

The target-snowflake loader sends data into Snowflake after it was pulled from a source using an extractor

Available Variants

Getting Started

Prerequisites

If you haven't already, follow the initial steps of the Getting Started guide:

  1. Install Meltano
  2. Create your Meltano project

Dependencies

A Snowflake FILE FORMAT object must exist prior to execution and is a required config input. You can use the sample SQL provided below:

CREATE FILE FORMAT {database}.{schema}.{file_format_name}
TYPE = 'CSV' ESCAPE='\\' FIELD_OPTIONALLY_ENCLOSED_BY='"';

See the documentation for more details on other optional objects and how to create them.

Installation and configuration

  1. Add the target-snowflake loader to your project using
    meltano add
    :
  2. meltano add loader target-snowflake
  3. Configure the target-snowflake settings using
    meltano config
    :
  4. meltano config target-snowflake set --interactive

Next steps

If you run into any issues, learn how to get help.

Capabilities

This plugin currently has no capabilities defined. If you know the capabilities required by this plugin, please contribute!

Settings

The target-snowflake settings that are known to Meltano are documented below. To quickly find the setting you're looking for, click on any setting name from the list:

You can also list these settings using

meltano config
with the list subcommand:

meltano config target-snowflake list

You can override these settings or specify additional ones in your meltano.yml by adding the settings key.

Please consider adding any settings you have defined locally to this definition on MeltanoHub by making a pull request to the YAML file that defines the settings for this plugin.

Account (account)

  • Environment variable: TARGET_SNOWFLAKE_ACCOUNT

Snowflake account name (i.e. rtXXXXX.eu-central-1)


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set account [value]

Database Name (dbname)

  • Environment variable: TARGET_SNOWFLAKE_DBNAME

Snowflake Database name


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set dbname [value]

User (user)

  • Environment variable: TARGET_SNOWFLAKE_USER

Snowflake User


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set user [value]

Password (password)

  • Environment variable: TARGET_SNOWFLAKE_PASSWORD

Snowflake Password


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set password [value]

Warehouse (warehouse)

  • Environment variable: TARGET_SNOWFLAKE_WAREHOUSE

Snowflake virtual warehouse name


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set warehouse [value]

File Format (file_format)

  • Environment variable: TARGET_SNOWFLAKE_FILE_FORMAT

The Snowflake file format object name which needs to be manually created as part of the requirements section of the docs. Has to be the fully qualified name including the schema. Refer to the Snowflake docs for more details.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set file_format [value]

Role (role)

  • Environment variable: TARGET_SNOWFLAKE_ROLE

Snowflake role to use. If not defined then the user's default role will be used.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set role [value]

AWS Access Key ID (aws_access_key_id)

  • Environment variable: TARGET_SNOWFLAKE_AWS_ACCESS_KEY_ID

S3 Access Key Id. If not provided, AWS_ACCESS_KEY_ID environment variable or IAM role will be used


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set aws_access_key_id [value]

AWS Secret Access Key (aws_secret_access_key)

  • Environment variable: TARGET_SNOWFLAKE_AWS_SECRET_ACCESS_KEY

S3 Secret Access Key. If not provided, AWS_SECRET_ACCESS_KEY environment variable or IAM role will be used


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set aws_secret_access_key [value]

AWS Session Token (aws_session_token)

  • Environment variable: TARGET_SNOWFLAKE_AWS_SESSION_TOKEN

AWS Session token. If not provided, AWS_SESSION_TOKEN environment variable will be used


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set aws_session_token [value]

AWS Profile (aws_profile)

  • Environment variable: TARGET_SNOWFLAKE_AWS_PROFILE

AWS profile name for profile based authentication. If not provided, AWS_PROFILE environment variable will be used.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set aws_profile [value]

Default Target Schema (default_target_schema)

  • Environment variable: TARGET_SNOWFLAKE_DEFAULT_TARGET_SCHEMA
  • Default Value: $MELTANO_EXTRACT__LOAD_SCHEMA

Note $MELTANO_EXTRACT__LOAD_SCHEMA will expand to the value of the load_schema extra for the extractor used in the pipeline, which defaults to the extractor's namespace, e.g. tap_gitlab for tap-gitlab. Values are automatically converted to uppercase before they're passed on to the plugin, so tap_gitlab becomes TAP_GITLAB.

Name of the schema where the tables will be created, without database prefix. If schema_mapping is not defined then every stream sent by the tap is loaded into this schema.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set default_target_schema [value]

S3 Bucket (s3_bucket)

  • Environment variable: TARGET_SNOWFLAKE_S3_BUCKET

S3 Bucket name


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set s3_bucket [value]

S3 Key Prefix (s3_key_prefix)

  • Environment variable: TARGET_SNOWFLAKE_S3_KEY_PREFIX

A static prefix before the generated S3 key names. Using prefixes you can upload files into specific directories in the S3 bucket.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set s3_key_prefix [value]

S3 Endpoint URL (s3_endpoint_url)

  • Environment variable: TARGET_SNOWFLAKE_S3_ENDPOINT_URL

The complete URL to use for the constructed client. This is allowing to use non-native s3 account.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set s3_endpoint_url [value]

S3 Region Name (s3_region_name)

  • Environment variable: TARGET_SNOWFLAKE_S3_REGION_NAME

Default region when creating new connections


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set s3_region_name [value]

S3 ACL (s3_acl)

  • Environment variable: TARGET_SNOWFLAKE_S3_ACL

S3 ACL name to set on the uploaded files


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set s3_acl [value]

Stage (stage)

  • Environment variable: TARGET_SNOWFLAKE_STAGE

Named external stage name created at pre-requirements section. Has to be a fully qualified name including the schema name


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set stage [value]

Batch Size Rows (batch_size_rows)

  • Environment variable: TARGET_SNOWFLAKE_BATCH_SIZE_ROWS
  • Default Value: 100000

Maximum number of rows in each batch. At the end of each batch, the rows in the batch are loaded into Snowflake.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set batch_size_rows [value]

Batch Wait Limit Seconds (batch_wait_limit_seconds)

  • Environment variable: TARGET_SNOWFLAKE_BATCH_WAIT_LIMIT_SECONDS

Maximum time to wait for batch to reach batch_size_rows.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set batch_wait_limit_seconds [value]

Flush All Streams (flush_all_streams)

  • Environment variable: TARGET_SNOWFLAKE_FLUSH_ALL_STREAMS
  • Default Value: false

Flush and load every stream into Snowflake when one batch is full. Warning: This may trigger the COPY command to use files with low number of records, and may cause performance problems.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set flush_all_streams [value]

Parallelism (parallelism)

  • Environment variable: TARGET_SNOWFLAKE_PARALLELISM
  • Default Value: 0

The number of threads used to flush tables. 0 will create a thread for each stream, up to parallelism_max. -1 will create a thread for each CPU core. Any other positive number will create that number of threads, up to parallelism_max.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set parallelism [value]

Parallelism Max (parallelism_max)

  • Environment variable: TARGET_SNOWFLAKE_PARALLELISM_MAX
  • Default Value: 16

Max number of parallel threads to use when flushing tables.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set parallelism_max [value]

Default Target Schema Select Permission (default_target_schema_select_permission)

  • Environment variable: TARGET_SNOWFLAKE_DEFAULT_TARGET_SCHEMA_SELECT_PERMISSION

Grant USAGE privilege on newly created schemas and grant SELECT privilege on newly created tables to a specific role or a list of roles. If schema_mapping is not defined then every stream sent by the tap is granted accordingly.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set default_target_schema_select_permission [value]

Schema Mapping (schema_mapping)

  • Environment variable: TARGET_SNOWFLAKE_SCHEMA_MAPPING

Useful if you want to load multiple streams from one tap to multiple Snowflake schemas.

If the tap sends the stream_id in <schema_name>-<table_name> format then this option overwrites the default_target_schema value.

Note, that using schema_mapping you can overwrite the default_target_schema_select_permission value to grant SELECT permissions to different groups per schemas or optionally you can create indices automatically for the replicated tables.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set schema_mapping [value]

Disable Table Cache (disable_table_cache)

  • Environment variable: TARGET_SNOWFLAKE_DISABLE_TABLE_CACHE
  • Default Value: false

By default the connector caches the available table structures in Snowflake at startup. In this way it doesn't need to run additional queries when ingesting data to check if altering the target tables is required. With disable_table_cache option you can turn off this caching. You will always see the most recent table structures but will cause an extra query runtime.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set disable_table_cache [value]

Client Side Encryption Master Key (client_side_encryption_master_key)

  • Environment variable: TARGET_SNOWFLAKE_CLIENT_SIDE_ENCRYPTION_MASTER_KEY

When this is defined, Client-Side Encryption is enabled. The data in S3 will be encrypted, No third parties, including Amazon AWS and any ISPs, can see data in the clear. Snowflake COPY command will decrypt the data once it's in Snowflake. The master key must be 256-bit length and must be encoded as base64 string.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set client_side_encryption_master_key [value]

Client Side Encryption Stage Object (client_side_encryption_stage_object)

  • Environment variable: TARGET_SNOWFLAKE_CLIENT_SIDE_ENCRYPTION_STAGE_OBJECT

Required when client_side_encryption_master_key is defined. The name of the encrypted stage object in Snowflake that created separately and using the same encryption master key.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set client_side_encryption_stage_object [value]

Add Metadata Columns (add_metadata_columns)

  • Environment variable: TARGET_SNOWFLAKE_ADD_METADATA_COLUMNS
  • Default Value: false

Metadata columns add extra row level information about data ingestions, (i.e. when was the row read in source, when was inserted or deleted in snowflake etc.) Metadata columns are creating automatically by adding extra columns to the tables with a column prefix _SDC_. The column names are following the stitch naming conventions documented at https://www.stitchdata.com/docs/data-structure/integration-schemas#sdc-columns. Enabling metadata columns will flag the deleted rows by setting the _SDC_DELETED_AT metadata column. Without the add_metadata_columns option the deleted rows from singer taps will not be recongisable in Snowflake.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set add_metadata_columns [value]

Hard Delete (hard_delete)

  • Environment variable: TARGET_SNOWFLAKE_HARD_DELETE
  • Default Value: false

When hard_delete option is true then DELETE SQL commands will be performed in Snowflake to delete rows in tables. It's achieved by continuously checking the _SDC_DELETED_AT metadata column sent by the singer tap. Due to deleting rows requires metadata columns, hard_delete option automatically enables the add_metadata_columns option as well.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set hard_delete [value]

Data Flattening Max Level (data_flattening_max_level)

  • Environment variable: TARGET_SNOWFLAKE_DATA_FLATTENING_MAX_LEVEL
  • Default Value: 0

Object type RECORD items from taps can be loaded into VARIANT columns as JSON (default) or we can flatten the schema by creating columns automatically. When value is 0 (default) then flattening functionality is turned off.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set data_flattening_max_level [value]

Primary Key Required (primary_key_required)

  • Environment variable: TARGET_SNOWFLAKE_PRIMARY_KEY_REQUIRED
  • Default Value: true

Log based and Incremental replications on tables with no Primary Key cause duplicates when merging UPDATE events. When set to true, stop loading data if no Primary Key is defined.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set primary_key_required [value]

Validate Records (validate_records)

  • Environment variable: TARGET_SNOWFLAKE_VALIDATE_RECORDS
  • Default Value: false

Validate every single record message to the corresponding JSON schema. This option is disabled by default and invalid RECORD messages will fail only at load time by Snowflake. Enabling this option will detect invalid records earlier but could cause performance degradation.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set validate_records [value]

Temporary Directory (temp_dir)

  • Environment variable: TARGET_SNOWFLAKE_TEMP_DIR

(Default: platform-dependent) Directory of temporary CSV files with RECORD messages.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set temp_dir [value]

No Compression (no_compression)

  • Environment variable: TARGET_SNOWFLAKE_NO_COMPRESSION
  • Default Value: false

Generate uncompressed CSV files when loading to Snowflake. Normally, by default GZIP compressed files are generated.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set no_compression [value]

Query Tag (query_tag)

  • Environment variable: TARGET_SNOWFLAKE_QUERY_TAG

Optional string to tag executed queries in Snowflake. Replaces tokens

schema and table with the appropriate values. The tags are displayed in the output of the Snowflake QUERY_HISTORY, QUERY_HISTORY_BY_* functions.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set query_tag [value]

Archive Load Files (archive_load_files)

  • Environment variable: TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES
  • Default Value: false

When enabled, the files loaded to Snowflake will also be stored in archive_load_files_s3_bucket under the key /{archive_load_files_s3_prefix}/{schema_name}/{table_name}/.

All archived files will have tap, schema, table and archived-by as S3 metadata keys.

When incremental replication is used, the archived files will also have the following S3 metadata keys - incremental-key, incremental-key-min and incremental-key-max.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set archive_load_files [value]

Archive Load Files S3 Prefix (archive_load_files_s3_prefix)

  • Environment variable: TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES_S3_PREFIX

When archive_load_files is enabled, the archived files will be placed in the archive S3 bucket under this prefix.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set archive_load_files_s3_prefix [value]

Archive Load Files S3 Bucket (archive_load_files_s3_bucket)

  • Environment variable: TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES_S3_BUCKET

When archive_load_files is enabled, the archived files will be placed in this bucket.


Configure this setting directly using the following Meltano command:

meltano config target-snowflake set archive_load_files_s3_bucket [value]

Something missing?

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Edit it on GitHub!

Looking for help?

If you're having trouble getting the target-snowflake loader to work, look for an existing issue in its repository, file a new issue, or join the Meltano Slack community and ask for help in the
#plugins-general
channel.

Install

meltano add loader target-snowflake

Maintenance Status

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Repo

https://github.com/transferwise/pipelinewise-target-snowflake
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  • Wise

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Keywords

  • database