schema
stringclasses 471
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stringlengths 0
203
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|---|---|---|---|
comet.json
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PrimitiveType
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Timestamp based on `RFC 1123 / RFC 822` patterns (Tue, 3 Jun 2008 11:05:30 GMT)
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{"const": "rfc_1123_date_time"}
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comet.json
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PrimitiveType
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date/time that match the 'yyyy-MM-dd HH:mm:ss' regex s (2019-12-31 23:59:02).
For epoch timestamp, set pattern attribute to 'epoch_second' or 'epoch_milli'
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{"const": "timestamp"}
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comet.json
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PrimitiveType
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Any floating value that match the '-?\d*\.{0,1}\d+' regex
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{"const": "decimal"}
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comet.json
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PrimitiveType
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Any attribute that has children. Set the array to true if this attribute is made of a list of attributes
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{"const": "struct"}
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comet.json
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IndexMapping
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{"const": "text"}
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comet.json
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IndexMapping
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{"const": "keyword"}
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comet.json
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IndexMapping
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{"const": "long"}
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comet.json
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IndexMapping
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{"const": "integer"}
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comet.json
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IndexMapping
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{"const": "short"}
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comet.json
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IndexMapping
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{"const": "byte"}
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comet.json
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IndexMapping
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{"const": "double"}
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comet.json
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IndexMapping
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{"const": "float"}
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comet.json
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IndexMapping
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{"const": "half_float"}
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comet.json
|
IndexMapping
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{"const": "scaled_float"}
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comet.json
|
IndexMapping
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{"const": "date"}
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comet.json
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IndexMapping
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{"const": "boolean"}
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comet.json
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IndexMapping
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{"const": "binary"}
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comet.json
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IndexMapping
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{"const": "integer_rang"}
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comet.json
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IndexMapping
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{"const": "float_range"}
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comet.json
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IndexMapping
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{"const": "long_range"}
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comet.json
|
IndexMapping
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{"const": "double_range"}
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comet.json
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IndexMapping
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{"const": "date_range"}
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comet.json
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IndexMapping
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{"const": "geo_point"}
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comet.json
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IndexMapping
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{"const": "geo_shape"}
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comet.json
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IndexMapping
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{"const": "ip"}
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comet.json
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IndexMapping
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{"const": "completion"}
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comet.json
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IndexMapping
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{"const": "token_count"}
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comet.json
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IndexMapping
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{"const": "object"}
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comet.json
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IndexMapping
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{"const": "array"}
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comet.json
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WriteMode
|
Append to or overwrite existing data
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{"type": "string", "oneOf": [{"const": "OVERWRITE"}, {"const": "APPEND"}, {"const": "ERROR_IF_EXISTS"}, {"const": "IGNORE"}]}
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comet.json
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WriteMode
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That data will overwrite the existing data or create it if it does not exist
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{"const": "OVERWRITE"}
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comet.json
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WriteMode
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Append the data to an existing table or create it if it does not exist
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{"const": "APPEND"}
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comet.json
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WriteMode
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Fail if teh table already exist
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{"const": "ERROR_IF_EXISTS"}
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comet.json
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WriteMode
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Do not save at all. Useful in interactive / test mode.
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{"const": "IGNORE"}
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comet.json
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UserType
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Service account
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{"const": "SA"}
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comet.json
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UserType
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End user
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{"const": "USER"}
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comet.json
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UserType
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Group of users / service accounts
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{"const": "GROUP"}
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comet.json
|
Trim
|
Remove all leading space chars from the input
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{"const": "LEFT"}
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comet.json
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Trim
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Remove all trailing spaces from the input
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{"const": "RIGHT"}
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comet.json
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Trim
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Remove all leading and trailing spaces from the input
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{"const": "BOTH"}
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comet.json
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Trim
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Do not remove leading or trailing spaces from the input
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{"const": "NONE"}
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comet.json
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TableDdl
|
DDL used to create a table
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{"type": "object", "properties": {"createSql": {"type": "string"}, "pingSql": {"type": "string"}}, "required": ["createSql"]}
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comet.json
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createSql
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SQL CREATE DDL statement
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{"type": "string"}
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comet.json
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pingSql
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How to test if the table exist.
Use the following statement by default: 'select count(*) from tableName where 1=0'
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{"type": "string"}
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comet.json
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TableType
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Table types supported by the Extract module
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{"type": "string", "oneOf": [{"const": "TABLE"}, {"const": "VIEW"}, {"const": "SYSTEM TABLE"}, {"const": "GLOBAL TEMPORARY"}, {"const": "LOCAL TEMPORARY"}, {"const": "ALIAS"}, {"const": "SYNONYM"}]}
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comet.json
|
TableType
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SQl Table
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{"const": "TABLE"}
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comet.json
|
TableType
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SQl View
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{"const": "VIEW"}
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comet.json
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TableType
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Database specific system table
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{"const": "SYSTEM TABLE"}
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comet.json
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TableType
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{"const": "GLOBAL TEMPORARY"}
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comet.json
|
TableType
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{"const": "LOCAL TEMPORARY"}
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comet.json
|
TableType
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Table alias
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{"const": "ALIAS"}
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comet.json
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TableType
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Table synonym
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{"const": "SYNONYM"}
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comet.json
|
Type
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Custom type definition. Custom types are defined in the types/types.comet.yml file
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{"type": "object", "properties": {"name": {"type": "string"}, "primitiveType": {}, "pattern": {"type": "string"}, "zone": {"type": "string"}, "sample": {"type": "string"}, "comment": {"type": "string"}, "indexMapping": {"type": "string"}, "ddlMapping": {}}, "required": ["name", "pattern", "primitiveType"]}
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comet.json
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name
|
unique id for this type
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{"type": "string"}
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comet.json
|
primitiveType
|
To what primitive type should this type be mapped.
This is the memory representation of the type, When saving, this primitive type is mapped to the database specific type
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{}
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comet.json
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pattern
|
Regex used to validate the input field
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{"type": "string"}
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comet.json
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zone
|
useful when parsing specific string:
- double: To parse a french decimal (comma as decimal separator) set it to fr_FR locale.
- decimal: to set the precision and scale of this number, '38,9' by default.
-
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{"type": "string"}
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comet.json
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sample
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This field makes sure that the pattern matches the value you want to match. This will be checked on startup
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{"type": "string"}
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comet.json
|
comment
|
Describes this type
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{"type": "string"}
|
comet.json
|
indexMapping
|
How this type is indexed in your datawarehouse
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{"type": "string"}
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comet.json
|
ddlMapping
|
Configure here the type mapping for each datawarehouse.\nWill be used when inferring DDL from schema.
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{}
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comet.json
|
Partition
|
Partition columns, no partitioning by default
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{"type": "object", "properties": {"sampling": {"type": "number"}, "attributes": {"type": "array", "items": {"type": "string"}}}, "required": []}
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comet.json
|
sampling
|
0.0 means no sampling, > 0 && < 1 means sample dataset, >=1 absolute number of partitions. Used exclusively on Hadoop & databricks warehouses
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{"type": "number"}
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comet.json
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items
|
Attributes used to partition de dataset.
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{"type": "string"}
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comet.json
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first
|
Zero based position of the first character for this attribute
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{"type": "number"}
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comet.json
|
last
|
Zero based position of the last character to include in this attribute
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{"type": "number"}
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comet.json
|
Connection
|
Connection
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{"type": "object", "properties": {"type": {"type": "string"}, "sparkFormat": {"type": "string"}, "mode": {}, "options": {}}, "required": ["type"]}
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comet.json
|
type
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aka jdbc, bigquery, snowflake, redshift ...
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{"type": "string"}
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comet.json
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sparkFormat
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Set only if you want to use the Spark engine
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{"type": "string"}
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comet.json
|
mode
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Used for JDBC connections only. Write mode, APPEND by default
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{}
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comet.json
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options
|
Connection options
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{}
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comet.json
|
RowLevelSecurity
|
Row level security policy to apply to the output data.
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{"type": "object", "properties": {"name": {"type": "string"}, "predicate": {"type": "string"}, "grants": {"type": "array", "items": {"type": "string"}}}, "required": ["name", "grants"]}
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comet.json
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name
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This Row Level Security unique name
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{"type": "string"}
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comet.json
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description
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Description for this access policy
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{"type": "string"}
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comet.json
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predicate
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The condition that goes to the WHERE clause and limit the visible rows.
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{"type": "string"}
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comet.json
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grants
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user / groups / service accounts to which this security level is applied.
ex : user:[email protected],group:[email protected],serviceAccount:[email protected]
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{"type": "array", "items": {"type": "string"}}
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comet.json
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AccessControlEntry
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Column level security policy to apply to the attribute.
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{"type": "object", "properties": {"role": {"type": "string"}, "grants": {"type": "array", "items": {"type": "string"}}}, "required": ["role", "grants"]}
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comet.json
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role
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This role to give to the granted users
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{"type": "string"}
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comet.json
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grants
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user / groups / service accounts to which this security level is applied.
ex : user:[email protected],group:[email protected],serviceAccount:[email protected]
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{"type": "array", "items": {"type": "string"}}
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comet.json
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key
|
list of attributes to join an existing and incoming dataset. Use renamed columns if any here.
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{"type": "array", "items": {"type": "string"}}
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comet.json
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delete
|
Optional valid delete condition on the incoming dataset. Use renamed column here.
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{"type": "string"}
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comet.json
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timestamp
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Timestamp column used to identify last version, if not specified currently ingested row is considered the last
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{"type": "string"}
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comet.json
|
queryFilter
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Useful when you want to merge only on a subset of the existing partitions, thus improving performance and reducing costs.
You may use here:
- Any SQL condition
- latest which will be translated to the last existing partition
- column in last(10) which will apply the merge on the last 10 partitions of your dataset.
last and latest assume that your table is partitioned by day.
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{"type": "string"}
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comet.json
|
Format
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DSV by default. Supported file formats are :\n- DSV : Delimiter-separated values file. Delimiter value is specified in the "separator" field.\n- POSITION : FIXED format file where values are located at an exact position in each line.\n- SIMPLE_JSON : For optimisation purpose, we differentiate JSON with top level values from JSON\n with deep level fields. SIMPLE_JSON are JSON files with top level fields only.\n- JSON : Deep JSON file. Use only when your json documents contain sub-documents, otherwise prefer to\n use SIMPLE_JSON since it is much faster.\n- XML : XML files
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{"type": "string", "oneOf": [{"const": "DSV"}, {"const": "POSITION"}, {"const": "JSON"}, {"const": "ARRAY_JSON"}, {"const": "SIMPLE_JSON"}, {"const": "XML"}]}
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comet.json
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Format
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any single or multiple character delimited file. Separator is specified in the separator field
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{"const": "DSV"}
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comet.json
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Format
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any fixed position file. Positions are specified in the position field
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{"const": "POSITION"}
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comet.json
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Format
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any deep json file.
To improve performance, prefer the SIMPLE_JSON format if your json documents are flat
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{"const": "JSON"}
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comet.json
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Format
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any json file containing an array of json objects.
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{"const": "ARRAY_JSON"}
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comet.json
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Format
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any flat json file.
To improve performance, prefer this format if your json documents are flat
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{"const": "SIMPLE_JSON"}
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comet.json
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Format
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any xml file. Use the metadata.xml.rowTag field to specify the root tag of your xml file
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{"const": "XML"}
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comet.json
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MapString
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Map of string
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{"type": "object", "additionalProperties": {"type": "string"}}
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comet.json
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MapConnection
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Map of connections
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{"type": "object", "additionalProperties": {}}
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comet.json
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MapJdbcEngine
|
Map of jdbc engines
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{"type": "object", "additionalProperties": {}}
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comet.json
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MapTableDdl
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Map of table ddl
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{"type": "object", "additionalProperties": {}}
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comet.json
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JdbcEngine
|
Jdbc engine
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{"type": "object", "properties": {"tables": {"type": "array", "items": {}}}}
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comet.json
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tables
|
List of all SQL create statements used to create audit tables for this JDBC engine.
Tables are created only if the execution of the pingSQL statement fails
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{"type": "array", "items": {}}
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comet.json
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options
|
Privacy strategies. The following default strategies are defined by default:
- none: Leave the data as is
- hide: replace the data with an empty string
- hideX("s", n): replace the string with n occurrences of the string 's'
- md5: Redact the data using the MD5 algorithm
- sha1: Redact the data using the SHA1 algorithm
- sha256: Redact the data using the SHA256 algorithm
- sha512: Redact the data using the SHA512 algorithm
- initials: keep only the first char of each word in the data
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{}
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comet.json
|
Internal
|
configure Spark internal options
|
{"type": "object", "properties": {"cacheStorageLevel": {"type": "string"}, "intermediateBigqueryFormat": {"type": "string"}, "temporaryGcsBucket": {"type": "string"}, "substituteVars": {"type": "boolean"}}}
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comet.json
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cacheStorageLevel
|
How the RDD are cached. Default is MEMORY_AND_DISK_SER.
Available options are (https://spark.apache.org/docs/latest/api/java/index.html?org/apache/spark/storage/StorageLevel.html):
- MEMORY_ONLY
- MEMORY_AND_DISK
- MEMORY_ONLY_SER
- MEMORY_AND_DISK_SER
- DISK_ONLY
- OFF_HEAP
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{"type": "string"}
|
comet.json
|
intermediateBigqueryFormat
|
May be parquet or ORC. Default is parquet. Used for BigQuery intermediate storage. Use ORC for for JSON files to keep the original data structure.
https://stackoverflow.com/questions/53674838/spark-writing-parquet-arraystring-converts-to-a-different-datatype-when-loadin
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{"type": "string"}
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