DataFrameReader.
jdbc
Construct a DataFrame representing the database table named table accessible via JDBC URL url and connection properties.
DataFrame
table
url
properties
Partitions of the table will be retrieved in parallel if either column or predicates is specified. lowerBound`, ``upperBound and numPartitions is needed when column is specified.
column
predicates
lowerBound`, ``upperBound
numPartitions
If both column and predicates are specified, column will be used.
Note
Don’t create too many partitions in parallel on a large cluster; otherwise Spark might crash your external database systems.
url – a JDBC URL of the form jdbc:subprotocol:subname
jdbc:subprotocol:subname
table – the name of the table
column – the name of a column of numeric, date, or timestamp type that will be used for partitioning; if this parameter is specified, then numPartitions, lowerBound (inclusive), and upperBound (exclusive) will form partition strides for generated WHERE clause expressions used to split the column column evenly
lowerBound
upperBound
lowerBound – the minimum value of column used to decide partition stride
upperBound – the maximum value of column used to decide partition stride
numPartitions – the number of partitions
predicates – a list of expressions suitable for inclusion in WHERE clauses; each one defines one partition of the DataFrame
properties – a dictionary of JDBC database connection arguments. Normally at least properties “user” and “password” with their corresponding values. For example { ‘user’ : ‘SYSTEM’, ‘password’ : ‘mypassword’ }
a DataFrame
New in version 1.4.