dse spark-sql

Starts the Spark SQL shell in DSE to interactively perform Spark SQL queries.

Starts the Spark SQL shell in DSE to interactively perform Spark SQL queries.

The Spark SQL shell in DSE automatically creates a Spark session and connects to the Spark SQL Thrift server to handle the underlying JDBC connections. See Using Spark SQL to query data.


dse spark-sql
Table 1. Legend
Syntax conventions Description
UPPERCASE Literal keyword.
Lowercase Not literal.
Italics Variable value. Replace with a valid option or user-defined value.
[ ] Optional. Square brackets ( [ ] ) surround optional command arguments. Do not type the square brackets.
( ) Group. Parentheses ( ( ) ) identify a group to choose from. Do not type the parentheses.
| Or. A vertical bar ( | ) separates alternative elements. Type any one of the elements. Do not type the vertical bar.
... Repeatable. An ellipsis ( ... ) indicates that you can repeat the syntax element as often as required.
'Literal string' Single quotation ( ' ) marks must surround literal strings in CQL statements. Use single quotation marks to preserve upper case.
{ key:value } Map collection. Braces ( { } ) enclose map collections or key value pairs. A colon separates the key and the value.
<datatype1,datatype2> Set, list, map, or tuple. Angle brackets ( < > ) enclose data types in a set, list, map, or tuple. Separate the data types with a comma.
cql_statement; End CQL statement. A semicolon ( ; ) terminates all CQL statements.
[ -- ] Separate the command line options from the command arguments with two hyphens ( -- ). This syntax is useful when arguments might be mistaken for command line options.
' <schema> ... </schema> ' Search CQL only: Single quotation marks ( ' ) surround an entire XML schema declaration.
@xml_entity='xml_entity_type' Search CQL only: Identify the entity and literal value to overwrite the XML element in the schema and solrconfig files.

This command accepts no parameters.


Start the Spark SQL shell

dse spark-sql
The log file is at /home/ubuntu/.spark-sql-shell.log
At the spark-sql prompt, you can interactively perform Spark SQL queries.