> ## Documentation Index > Fetch the complete documentation index at: https://docs.maia.ai/llms.txt > Use this file to discover all available pages before exploring further. # CSV Load export const filetype_0 = ".csv" export const ComponentMetadata = ({warehouses, unsupportedWarehouses = [], componentType, connectionInputs, connectionOutputs}) => { const allWarehouses = [...warehouses.map(w => ({ name: w, supported: true })), ...unsupportedWarehouses.map(w => ({ name: w, supported: false }))]; return

Project Availability	{allWarehouses.map((w, i) => {w.name} {w.supported ? '✅' : '❌'} )}
Component Type	{componentType}
Connection Inputs	{connectionInputs}
Connection Outputs	{connectionOutputs}

; }; The CSV Load orchestration component loads data into a table from one or more CSV files. The component automatically infers the schema from the structure of the selected file(s), creates the corresponding table, and then loads the data into the table. ## Use cases CSV Load suits a range of data ingestion scenarios. For example, you can use this component to: * Load daily sales or transaction exports from a CRM or ERP system to make them available for downstream reporting. * Ingest historical records from a legacy system as part of a migration to a cloud data warehouse. * Load partner-supplied reference data—such as product catalogs, pricing lists, or exchange rate tables—delivered as recurring flat files. * Load survey or form response exports into a staging table to combine with existing customer data for analysis. * Process batch files deposited into cloud storage on a schedule, such as nightly inventory snapshots or weekly fulfillment reports. You can authorize this component using either of these two methods: * **Cloud Provider Credentials**: By default, explicit [Cloud Provider Credentials](/docs/guides/cloud-credentials) are used to facilitate cross-account or cross-cloud data loads. * **Agent Identity**: If cloud provider credentials are not specified, the component attempts to use the Matillion Agent's native service identity to access the source data. *** ## Properties A human-readable name for the component. ### Connect * **Snowflake Managed:** Load your file from a Snowflake internal stage. * **S3:** Load your file from an S3 bucket. * **Google Cloud Storage:** Load your file from a Google Cloud Storage bucket. * **Azure Blob Storage:** Load your file from an Azure Blob Storage container. {/* */} Select a staging area for the data. The special value \[New Stage] will create a temporary stage to be used for loading the data when the corresponding parameter values are provided. The options in this drop-down menu depend on the values you select for the `Database` and `Schema` parameters. If you change these values, the list of available options updates automatically, and the previously selected option may become invalid. When \[New Stage] is selected, the component uses the [cloud credentials](/docs/guides/cloud-credentials) configured for your environment to access the required resources. A stage may include directories. The user has the option to browse and select files from a specific directory path, for example, `/Example/Path`. If this is left blank, and if the **Pattern** parameter is also empty, all files from the stage will be loaded. To retrieve the intended files, use the file explorer to enter the container path where the S3 bucket is located, or select from the list of S3 buckets. This must have the format `s3:///`. {/* */} Decide how the files are encrypted inside the S3 bucket. This property is available when using an existing Amazon S3 location for staging. * **Client Side Encryption:** Encrypt the data according to a client-side master key. For more information, read [Protecting data using client-side encryption](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingClientSideEncryption.html). * **KMS Encryption:** Encrypt the data according to a key stored on KMS. For more information, read [Using server-side encryption with AWS KMS keys](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.html). * **S3 Encryption:** Encrypt the data according to a key stored on an S3 bucket. For more information, read [Using server-side encryption with Amazon S3-managed encryption keys (SSE-S3)](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingServerSideEncryption.html). * **None:** No encryption. {/* */} The ID of the KMS encryption key you have chosen to use in the `Encryption` property. Only available when `Encryption` is set to **KMS Encryption**. {/* */} The [secret definition](/docs/guides/secrets-and-secret-definitions) denoting your master key for client-side encryption. Your password should be saved as a secret definition before using this component. Only available when `Encryption` is set to **Client Side Encryption**. Select the storage integration. Storage integrations are required to permit Snowflake to read from and write to a cloud storage location. Integrations must be set up in advance and configured to support Google Cloud Storage. For more information, read [Create storage integration](https://docs.snowflake.com/en/sql-reference/sql/create-storage-integration). {/* */} To retrieve the intended files, use the file explorer to enter the container path where the Google Cloud Storage bucket is located, or select from the list of Google Cloud Storage buckets. This must have the format `gs:///`. To retrieve the intended files, use the file explorer to enter the container path where the Azure Storage account is located, or select from the list of storage accounts. This must have the format `azure:///`. {/* */} A valid regular expression (regex) to match part of a file's path or name. Files that match the pattern will be included in the load. If this parameter is left empty, the component automatically uses the pattern `*`, which matches all files within the specified `Staged file path` or `Stage` parameters. The pattern applies to the entire file path, not just the directory defined in `Staged file path`. The subfolder containing the object to load must be included here. * Only CSV files are supported. * Ensure that the pattern entered correctly targets the files you intend to load. * **S3:** Load your file from an S3 bucket. * **Google Cloud Storage:** Load your file from a Google Cloud Storage bucket. * **Azure Blob Storage:** Load your file from an Azure Blob Storage container. {/* */} To retrieve the intended files, use the file explorer to enter the container path where the S3 bucket is located, or select from the list of S3 buckets. This must have the format `s3:///`. {/* */} {/* */} To retrieve the intended files, use the file explorer to enter the container path where the Google Cloud Storage bucket is located, or select from the list of Google Cloud Storage buckets. This must have the format `gs:///`. For this to work, an external location with access to the specified location must be configured. For more information, read [External Locations | Databricks on AWS](https://docs.databricks.com/aws/en/sql/language-manual/sql-ref-external-locations). {/* */} {/* */} To retrieve the intended files, use the file explorer to enter the container path where the Azure Storage account is located, or select from the list of storage accounts. This must have the format `azure:///`. {/* */} {/* */} A valid glob pattern to match part of a file's path or name. Files that match the pattern will be included in the load. If this parameter is left empty, the component automatically uses the pattern `*`, which matches all files within the specified location parameters. The pattern applies to the entire file path, not just the directory defined in the location parameter. * Only CSV files are supported. * Ensure that the pattern entered correctly targets the files you intend to load. Select **Google Cloud Storage** to load your file from a Google Cloud Storage bucket. To retrieve the intended files, use the file explorer to enter the container path where the Google Cloud Storage bucket is located, or select from the list of Google Cloud Storage buckets. This must have the format `gs:///`. Filter for specific files by their file name, including their file extension. You can use wildcards in the file name, for example `prefix_*{filetype}`. If this field is left empty, all {filetype_0} files at the specified Google Storage URL location are loaded. If the specified Google Storage URL location contains a `*`, you can't apply a file filter. ### Configure The default value is set to `[New File Format]`. Specify a file format, and a temporary format with those settings will be used when the component runs. Alternatively, select a pre-made file format. {/* */} Select the compression algorithm used on the file being loaded. The default setting is AUTO. {/* */} Input a delimiter for records. This can be one or more single-byte or multibyte characters that separate records in an input file. Accepted values include: leaving the field empty; a newline character `\` or its hex equivalent `0x0a`; a carriage return `\\r` or its hex equivalent `0x0d`. Also accepts a value of NONE. If you set the **Skip Header** to a value such as 1, then you should use a record delimiter that includes a line feed or carriage return, such as `\` or `\\r`. Otherwise, your entire file will be interpreted as the header row, and no data will be loaded. The specified delimiter must be a valid UTF-8 character and not a random sequence of bytes. Do not specify characters used for other file type options such as **Escape** or **Escape unenclosed field**. The default (if the field is left blank) is a newline character. {/* */} Input a delimiter for fields. This can be one or more single-byte or multibyte characters that separate fields in an input file. Accepted characters include common escape sequences, octal values (prefixed by \\), or hex values (prefixed by 0x). Also accepts a value of NONE. This delimiter is limited to a maximum of 20 characters. While multi-character delimiters are supported, the field delimiter cannot be a substring of the record delimiter, and vice versa. For example, if the field delimiter is "aa", the record delimiter cannot be "aabb". The specified delimiter must be a valid UTF-8 character and not a random sequence of bytes. Do not specify characters used for other file type options such as **Escape** or **Escape unenclosed field**. The Default setting is a comma: `,`. {/* */} Specify whether the first row header should be used to define the column names of the resulting table. For this option to work, the **Match by column name** parameter must be set to either `CASE_SENSITIVE` or `CASE_INSENSITIVE`. The **Skip Header** option isn't supported if this parameter is set to true. The default setting is false. {/* */} Specify the number of rows to skip. The default is 0. If **Skip header** is used, the value of the record delimiter will not be used to determine where the header line is. Instead, the specified number of CRLF will be skipped. For example, if the value of **Skip header** = 1, skips to the first CRLF that it finds. If you have set the **Field delimiter** property to be a single character without a CRLF, then skips to the end of the file (treating the entire file as a header). {/* */} When **True**, ignores blank lines that only contain a line feed in a data file and does not try to load them. Default setting is **False**. {/* */} Specify a single character to be used as the escape character for field values that are enclosed. Default is NONE. {/* */} Specify a single character to be used as the escape character for unenclosed field values only. Default is `\\`. If you have set a value in the property **Field optionally enclosed**, all fields will become enclosed, rendering the **Escape unenclosed field** property redundant, in which case, it will be ignored. {/* */} When True, removes whitespace from fields. Default setting is False. {/* */} Specify a character used to enclose strings. The value can be NONE, single quote character `'`, or double quote character `"`. To use the single quote character, use the octal or hex representation `0x27` or the double single-quoted escape `''`. Default is NONE. When a field contains one of these characters, escape the field using the same character. For example, to escape a string like this: 1 "2" 3, use double quotation to escape, like this: 1 ""2"" 3. {/* */} Specify one or more strings (one string per row of the table) to convert to NULL values. When one of these strings is encountered in the file, it is replaced with an SQL NULL value for that field in the loaded table. Click + to add a string. {/* */} When True, generates an error if the number of delimited columns in an input file does not match the number of columns in the corresponding table. When False (default), an error is not generated and the load continues. If the file is successfully loaded in this case: * Where the input file contains records with more fields than columns in the table, the matching fields are loaded in order of occurrence in the file, and the remaining fields are not loaded. * Where the input file contains records with fewer fields than columns in the table, the non-matching columns in the table are loaded with NULL values. {/* */} When True, inserts NULL values for empty fields in an input file. This is the default setting. {/* */} Snowflake replaces invalid UTF-8 characters with the Unicode replacement character. When False (default), the load operation produces an error when invalid UTF-8 character encoding is detected. {/* */} Select the string that specifies the character set of the source data when loading data into a table. Refer to the Snowflake documentation for more information. Specify a single character that is used to escape special characters within a field value during parsing. {/* */} When set to Yes, corrupt input files are skipped and not included in the load. {/* */} When set to Yes, files that cannot be found are ignored during the load process. {/* */} An optional timestamp as a filter to only ingest files that have a modification timestamp **after** the provided timestamp. {/* */} An optional timestamp as a filter to only ingest files that have a modification timestamp **before** the provided timestamp. {/* */} When set to **Yes**, files are read recursively from all subdirectories under the specified path. When enabled, partition inference is disabled. To control which files are loaded, use the **Glob pattern** property instead. {/* */} Enter a location where information about bad or malformed CSV records should be written. {/* */} Define a single character used to escape the escape character for quoted values. {/* */} Define a line-comment character. When this character appears at the start of a line, the line is ignored. Use `\0` to disable comment handling. {/* */} Describe the format of date values in the data files to be loaded. For example, `yyyy-MM-dd`. {/* */} Specify the string representation of an empty value in the input data. {/* */} Select the character encoding to use when reading the input files. {/* */} When set to **Yes**, the defined or inferred schema is enforced while reading the CSV data. {/* */} Select **Yes** to use the first line of the file as column names. {/* */} When **Yes**, removes whitespace from the beginning of fields. {/* */} When **Yes**, removes whitespace from the end of fields. {/* */} Specify the character or sequence of characters used to separate individual records (rows) in the CSV file. {/* */} Sets the locale for date and timestamp parsing. The locale should be in BCP 47 language tag format (e.g., `en-US`). {/* */} Defines the maximum number of characters allowed for any given value being read. {/* */} Defines the maximum number of columns a CSV record can have. {/* */} When set to Yes, schemas from all input files are merged during the load. {/* */} Controls how the parser handles corrupt or malformed records. Options include: * **PERMISSIVE:** Tries to parse all lines; nulls are inserted for missing tokens and extra tokens are ignored. * **DROPMALFORMED:** Drops lines that contain malformed records. * **FAILFAST:** Throws an exception when it encounters a corrupted record. {/* */} If **Yes**, will parse records which may span multiple lines. {/* */} Sets the string representation of a non-number (NaN) value. {/* */} Sets the string representation of negative infinity. {/* */} Sets the string representation of a null value. {/* */} Sets the string representation of positive infinity. {/* */} If **Yes**, attempts to infer date columns instead of timestamp columns during schema inference. {/* */} Sets a single character used for escaping quoted values where the separator can be part of the value. {/* */} If **Yes**, column names will be case-sensitive during parsing. {/* */} Enter the delimiter character used to separate fields in the CSV file. This can be one or more single-byte or multibyte characters that separate fields in an input file. Accepted characters include common escape sequences, octal values (prefixed by `\\`), or hex values (prefixed by `0x`). This delimiter is limited to a maximum of 20 characters. The specified delimiter must be a valid UTF-8 character and not a random sequence of bytes. {/* */} Enter the number of rows to skip at the beginning of each file before parsing starts. {/* */} Describe the format of timestamp values in the data files to be loaded. {/* */} Sets the timezone to use when parsing timestamps. {/* */} Select how unescaped quotes are handled during parsing. * **STOP\_AT\_CLOSING\_QUOTE:** Stops parsing at the first closing quote encountered. * **BACK\_TO\_DELIMITER:** Returns to the delimiter to parse the value. * **STOP\_AT\_DELIMITER:** Stops at the delimiter. * **SKIP\_VALUE:** Skips the value. * **RAISE\_ERROR:** Raises an error. The character used to separate fields in the CSV file. For example, use `,` for comma-separated files or `\t` for tab-delimited files. Define how date values are formatted in your files, for example `MM/DD/YYYY`. If you leave this blank, the default format `YY-MM-DD` is used. Define how date values are formatted in your files, for example `MM/DD/YYYY HH24:MI:SS.FF3`. If you leave this blank, the default format `YYYY-MM-DD HH:MM:SS[.SSSSSS]` is used. Define how time values are formatted in your files, for example `HH24:MI:SS.FF3`. If you leave this blank, the default format `HH:MM:SS[.SSSSSS]` is used. Define how timestamp values are formatted in your files, for example `MM/DD/YYYY HH24:MI:SS.FF3`. If you leave this blank, Google BigQuery attempts to parse timestamp values automatically. Select how characters are encoded in your file. The number of rows at the top of the file to skip before reading data. For example, enter `1` to skip a header row. If you leave this blank, no rows are skipped. The character used to enclose field values in the CSV file. If your data contains quoted newline characters, set **Allow quoted newlines** to **Yes**. The string that represents NULL values in your file, for example, `\N` or `NULL`. When set to **Yes**, allows newline characters within quoted string fields in CSV files. When set to **Yes**, rows that are missing trailing optional columns are accepted. Missing values are treated as NULL. The default time zone to apply when parsing timestamp values that do not include a specific time zone. For example, `America/New_York` or `UTC+05:30`. If you leave this blank, UTC is used. The maximum number of bad records to ignore before returning an error. A record is considered bad if it cannot be parsed. For example, enter `10` to allow up to 10 unparseable rows before the load fails. If you leave this blank, the load will fail if there are any bad records. When set to **Yes**, extra fields in the file that are not present in the table schema are silently ignored. When set to **No**, extra fields cause the load to fail. Select how columns in the source file are matched to columns in the destination table. * **Position:** Columns are matched by their position in the file and the table schema. This assumes that the columns are in the same order in the file and table schema. * **Name:** Columns are matched by their name. This assumes that the header row contains column names. The column order in the file does not need to match the table schema. Controls the naming rules applied to columns when loading data. * **Strict:** Column names must conform to standard Google BigQuery [column naming](https://docs.cloud.google.com/bigquery/docs/schemas#column_names) rules. * **Allow flexible names:** Allows [flexible column names](https://docs.cloud.google.com/bigquery/docs/schemas#flexible-column-names) that would otherwise be invalid, such as names containing spaces or special characters. ### Destination {/* */} {/* */} {/* */} Specify the name of the newly created or existing table to load data into. The table will be created according to the `Load strategy` you select below. {/* */} * **Replace:** If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run. * **Truncate and Insert:** Each time the pipeline runs, two operations are performed: first, the table is truncated, meaning all existing rows are deleted. Then, your new rows are inserted. The table itself is never destroyed and recreated. * **Fail if Exists:** If the specified table name already exists, this pipeline will fail to run, and no data will be copied to the table. * **Append:** If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It's appended onto the end of the existing data in the table. If the specified table name doesn't exist, then an error message will appear and the table is not created. You must **always** provide a table name. {/* */} {/* */} The name of the table to be created. The table will be created according to the `Load strategy` you select below. {/* */} * **Replace:** If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run. * **Truncate and Insert:** Each time the pipeline runs, two operations are performed: first, the table is truncated, meaning all existing rows are deleted. Then, your new rows are inserted. The table itself is never destroyed and recreated. * **Fail if Exists:** If the specified table name already exists, this pipeline will fail to run, and no data will be copied to the table. * **Append:** If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It's appended onto the end of the existing data in the table. If the specified table name doesn't exist, then an error message will appear and the table is not created. You must **always** provide a table name. If not specified, the default is **Fail if Exists**. Databricks uses `COPY INTO`, which is idempotent. This means it tracks which source files have already been loaded into the target Delta table and skips them on subsequent runs. Enabling **Force load** overrides this behavior for the **Truncate and Insert** and **Append** load strategies, causing all matching source files to be reprocessed. Select the ID of the Google Cloud Platform project to load data into. The special value `[Environment Default]` uses the project defined in the environment. Select the Google BigQuery dataset to load data into. The special value `[Environment Default]` uses the dataset defined in the environment. The name of the table to be created in your Google BigQuery project. You can use a [Table Input](/docs/components/table-input) component in a transformation pipeline to access and transform this data after it has been loaded. Define what happens if the table name already exists in the specified destination. * **Replace:** If the specified table name already exists, that table will be destroyed and replaced by the table created during this pipeline run. * **Truncate and Insert:** Each time the pipeline runs, two operations are performed: first, the table is truncated, meaning all existing rows are deleted. Then, your new rows are inserted. The table itself is never destroyed and recreated. * **Fail if Exists:** If the specified table name already exists, this pipeline will fail to run. * **Append:** If the specified table name already exists, then the data is inserted without altering or deleting the existing data in the table. It's appended onto the end of the existing data in the table. If the specified table name doesn't exist, then the table will be created, and your data will be inserted into the table. ### Advanced Settings Specify the number of errors or the percentage of errors required to skip the file. This parameter only accepts integer characters. `%` is not accepted. Specify percentages as a number only. This parameter is only available when `On Error` is set to either **Skip File When n Errors** or **Skip File When n% Errors**. {/* */} Specify the maximum size, in bytes, of data to be loaded for a given COPY statement. If the maximum is exceeded, the COPY operation discontinues loading files. For more information, refer to the Snowflake documentation. {/* */} When True, purges data files after the data is successfully loaded. Default setting is False. {/* */} Specify whether to load semi-structured data into columns in the target table that match corresponding columns represented in the data. * **Case Insensitive:** Load semi-structured data into columns in the target table that match corresponding columns represented in the data. Column names should be case-insensitive. * **Case Sensitive:** Load semi-structured data into columns in the target table that match corresponding columns represented in the data. Column names should be case-sensitive. * **None:** The COPY operation loads the semi-structured data into a variant column or, if a query is included in the COPY statement, transforms the data. {/* */} When True, strings are automatically truncated to the target column length. When False (default), the COPY statement produces an error if a loaded string exceeds the target column length. {/* */} When True, loads all files, regardless of whether they have been loaded previously and haven't changed since they were loaded. Default setting is False. When set to True, this option reloads files and can lead to duplicated data in a table. When True, loads all files, regardless of whether they have been loaded previously and haven't changed since they were loaded. Default setting is False. When set to True, this option reloads files and can lead to duplicated data in a table. The `Load strategy` in the destination needs to be **Truncate and Insert** or **Append** for this to work. Select the rounding mode to use when storing numeric data types. For more information, read the Google BigQuery [RoundingMode](https://docs.cloud.google.com/bigquery/docs/schemas#rounding_mode) documentation. * `ROUND_HALF_AWAY_FROM_ZERO` rounds half values away from zero. * `ROUND_HALF_EVEN` rounds half values to the nearest even value.