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

Alternative variants #

Multiple variants of target-snowflake are available. This document describes the default transferwise variant, which is recommended for new users.

Alternative variants are:

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
  3. Add an extractor to pull data from a source

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 : 

    meltano add loader target-snowflake
  2. Configure the settings below using meltano config .

Next steps #

Follow the remaining steps of the Getting Started guide:

  1. Run a data integration (EL) pipeline
If you run into any issues, learn how to get help.

Capabilities #

Settings #

target-snowflake requires the configuration of the following settings:

The settings for loader target-snowflake that are known to Meltano are documented below. To quickly find the setting you're looking for, use the Table of Contents at the top of the page.

Account (account) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set account <account>

export TARGET_SNOWFLAKE_ACCOUNT=<account>

Database Name (dbname) #

Snowflake Database name

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set dbname <dbname>

export TARGET_SNOWFLAKE_DBNAME=<dbname>

User (user) #

Snowflake User

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set user <user>

export TARGET_SNOWFLAKE_USER=<user>

Password (password) #

Snowflake Password

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set password <password>

export TARGET_SNOWFLAKE_PASSWORD=<password>

Warehouse (warehouse) #

Snowflake virtual warehouse name

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set warehouse <warehouse>

export TARGET_SNOWFLAKE_WAREHOUSE=<warehouse>

File Format (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set file_format <file_format>

export TARGET_SNOWFLAKE_FILE_FORMAT=<file_format>

Role (role) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set role <role>

export TARGET_SNOWFLAKE_ROLE=<role>

AWS Access Key ID (aws_access_key_id) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set aws_access_key_id <aws_access_key_id>

export TARGET_SNOWFLAKE_AWS_ACCESS_KEY_ID=<aws_access_key_id>

AWS Secret Access Key (aws_secret_access_key) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set aws_secret_access_key <aws_secret_access_key>

export TARGET_SNOWFLAKE_AWS_SECRET_ACCESS_KEY=<aws_secret_access_key>

AWS Session Token (aws_session_token) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set aws_session_token <aws_session_token>

export TARGET_SNOWFLAKE_AWS_SESSION_TOKEN=<aws_session_token>

AWS Profile (aws_profile) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set aws_profile <aws_profile>

export TARGET_SNOWFLAKE_AWS_PROFILE=<aws_profile>

Default Target Schema (default_target_schema) #

  • Environment variable: TARGET_SNOWFLAKE_DEFAULT_TARGET_SCHEMA
  • Default: $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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set default_target_schema <default_target_schema>

export TARGET_SNOWFLAKE_DEFAULT_TARGET_SCHEMA=<default_target_schema>

S3 Bucket (s3_bucket) #

S3 Bucket name

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set s3_bucket <s3_bucket>

export TARGET_SNOWFLAKE_S3_BUCKET=<s3_bucket>

S3 Key Prefix (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set s3_key_prefix <s3_key_prefix>

export TARGET_SNOWFLAKE_S3_KEY_PREFIX=<s3_key_prefix>

S3 Endpoint URL (s3_endpoint_url) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set s3_endpoint_url <s3_endpoint_url>

export TARGET_SNOWFLAKE_S3_ENDPOINT_URL=<s3_endpoint_url>

S3 Region Name (s3_region_name) #

Default region when creating new connections

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set s3_region_name <s3_region_name>

export TARGET_SNOWFLAKE_S3_REGION_NAME=<s3_region_name>

S3 ACL (s3_acl) #

S3 ACL name to set on the uploaded files

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set s3_acl <s3_acl>

export TARGET_SNOWFLAKE_S3_ACL=<s3_acl>

Stage (stage) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set stage <stage>

export TARGET_SNOWFLAKE_STAGE=<stage>

Batch Size Rows (batch_size_rows) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set batch_size_rows 100000

export TARGET_SNOWFLAKE_BATCH_SIZE_ROWS=100000

Batch Wait Limit Seconds (batch_wait_limit_seconds) #

Maximum time to wait for batch to reach batch_size_rows.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set batch_wait_limit_seconds 1234

export TARGET_SNOWFLAKE_BATCH_WAIT_LIMIT_SECONDS=1234

Flush All Streams (flush_all_streams) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set flush_all_streams true

export TARGET_SNOWFLAKE_FLUSH_ALL_STREAMS=true

Parallelism (parallelism) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set parallelism 0

export TARGET_SNOWFLAKE_PARALLELISM=0

Parallelism Max (parallelism_max) #

Max number of parallel threads to use when flushing tables.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set parallelism_max 16

export TARGET_SNOWFLAKE_PARALLELISM_MAX=16

Default Target Schema Select Permission (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set default_target_schema_select_permission <default_target_schema_select_permission>

export TARGET_SNOWFLAKE_DEFAULT_TARGET_SCHEMA_SELECT_PERMISSION=<default_target_schema_select_permission>

Schema Mapping (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set schema_mapping '{...}'

export TARGET_SNOWFLAKE_SCHEMA_MAPPING='{...}'

Disable Table Cache (disable_table_cache) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set disable_table_cache true

export TARGET_SNOWFLAKE_DISABLE_TABLE_CACHE=true

Client Side Encryption Master Key (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set client_side_encryption_master_key <client_side_encryption_master_key>

export TARGET_SNOWFLAKE_CLIENT_SIDE_ENCRYPTION_MASTER_KEY=<client_side_encryption_master_key>

Client Side Encryption Stage Object (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set client_side_encryption_stage_object <client_side_encryption_stage_object>

export TARGET_SNOWFLAKE_CLIENT_SIDE_ENCRYPTION_STAGE_OBJECT=<client_side_encryption_stage_object>

Add Metadata Columns (add_metadata_columns) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set add_metadata_columns true

export TARGET_SNOWFLAKE_ADD_METADATA_COLUMNS=true

Hard Delete (hard_delete) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set hard_delete true

export TARGET_SNOWFLAKE_HARD_DELETE=true

Data Flattening Max Level (data_flattening_max_level) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set data_flattening_max_level 0

export TARGET_SNOWFLAKE_DATA_FLATTENING_MAX_LEVEL=0

Primary Key Required (primary_key_required) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set primary_key_required false

export TARGET_SNOWFLAKE_PRIMARY_KEY_REQUIRED=false

Validate Records (validate_records) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set validate_records true

export TARGET_SNOWFLAKE_VALIDATE_RECORDS=true

Temporary Directory (temp_dir) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set temp_dir <temp_dir>

export TARGET_SNOWFLAKE_TEMP_DIR=<temp_dir>

No Compression (no_compression) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set no_compression true

export TARGET_SNOWFLAKE_NO_COMPRESSION=true

Query Tag (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set query_tag <query_tag>

export TARGET_SNOWFLAKE_QUERY_TAG=<query_tag>

Archive Load Files (archive_load_files) #

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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set archive_load_files true

export TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES=true

Archive Load Files S3 Prefix (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.

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set archive_load_files_s3_prefix <archive_load_files_s3_prefix>

export TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES_S3_PREFIX=<archive_load_files_s3_prefix>

Archive Load Files S3 Bucket (archive_load_files_s3_bucket) #

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

How to use #

Manage this setting using meltano config or an environment variable: 

meltano config target-snowflake set archive_load_files_s3_bucket <archive_load_files_s3_bucket>

export TARGET_SNOWFLAKE_ARCHIVE_LOAD_FILES_S3_BUCKET=<archive_load_files_s3_bucket>

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.

Found an issue on this page? #

This page is generated from a YAML file that you can contribute changes to. Edit it on GitHub!