19.1. Release 0.152.1-t

Presto 0.152.1-t is equivalent to Presto release 0.152.1, with some additional features and patches.


  • LDAP Authentication


  • Support correlated scalar aggregation subqueries
  • Support correlated scalar subqueries
  • Additional prepared statement syntax: DESCRIBE INPUT and DESCRIBE OUTPUT

Data Types

  • Additional Varchar(x) and Char(x) function implementations
  • Additional Decimal functions implementations


  • Installation of Presto via Presto Admin
  • Presto Tuning Guide


  • Faster Decimal implementation
  • Move certain filters in the WHERE clauses to be executed as part of the INNER JOIN rather than a filter after the join. For example: SELECT * FROM t t1 JOIN t t2 ON t1.a = t2.a WHERE (t1.b+t2.b)*5 > 100000000
  • Code generation for joins with filters
  • Merge non-identical windows (for the same partition by and order by but different frame)
  • Add support for running regular expression functions using the more efficent re2j-td library by setting the session variable regex_library to RE2J. The memory footprint can be adjusted by setting re2j_dfa_states_limit. Additionally, the number of times the re2j library falls back from its DFA algorithm to the NFA algorithm (due to hitting the states limit) before immediately starting with the NFA algorithm can be set with the re2j_dfa_retries session variable.

Unsupported Functionality

Some functionality from Presto 0.152 may work but is not officially supported by Teradata.

  • The installation method as documented on prestodb.io.
  • Web Connector for Tableau
  • The following connectors:
    • Cassandra Connector
    • Kafka Connector
    • Local File Connector
    • MongoDB Connector
    • Redis Connector

SQL/DML/DDL Limitations

  • The SQL keyword end is used as a column name in system.runtime.queries, so in order to query from that column, end must be wrapped in quotes
  • NATURAL JOIN is not supported
  • LIMIT ALL and OFFSET are not supported

Hive Connector Limitations

Teradata supports data stored in the following formats:

  • Text files
  • ORC

TIMESTAMP limitations

Presto supports a granularity of milliseconds for the TIMESTAMP datatype, while Hive supports microseconds.

TIMESTAMP values in tables are parsed according to the server’s timezone. If this is not what you want, you must start Presto in the UTC timezone. To do this, set the JVM timezone to UTC: -Duser.timezone=UTC and also add the following property in the Hive connector properties file: hive.time-zone=UTC.

Presto’s method for declaring timestamps with/with out timezone is not sql standard. In Presto, both are declared using the word TIMESTAMP, e.g. TIMESTAMP '2003-12-10 10:32:02.1212' or TIMESTAMP '2003-12-10 10:32:02.1212 UTC'. The timestamp is determined to be with or without timezone depending on whether you include a time zone at the end of the timestamp. In other systems, timestamps are explicitly declared as TIMESTAMP WITH TIME ZONE or TIMESTAMP WITHOUT TIME ZONE (with TIMESTAMP being an alias for one of them). In these systems, if you declare a TIMESTAMP WITHOUT TIMEZONE, and your string has a timezone at the end, it is silently ignored. If you declare a TIMESTAMP WITH TIME ZONE and no time zone is included, the string is interpreted in the user time zone.

INSERT INTO ... VALUES limitations

The data types must be exact, i.e. must use 2.0 for double, cast('2015-1-1' as date) for date, and you must supply a value for every column.

INSERT INTO ... SELECT limitations

INSERT INTO creates unreadable data (unreadable both by Hive and Presto) if a Hive table has a schema for which Presto only interprets some of the columns (e.g. due to unsupported data types). This is because the generated file on HDFS will not match the Hive table schema.

If called through JDBC, executeUpdate does not return the count of rows inserted.

Hive Parquet Issues

PARQUET support in Hive imposes more limitations than the other file types.

DATE and BINARY datatypes are not supported

Teradata JDBC Driver

The Teradata JDBC driver does not support batch queries.

PostgreSQL and MySQL Connectors Limitations

Known Bugs

PostgreSQL connector describe table reports Table has no supported column types inappropriately. https://github.com/facebook/presto/issues/4082


Presto connects to MySQL and PostgreSQL using the credentials specified in the properties file. The credentials are used to authenticate the users while establishing the connection. Presto runs queries as the “presto” service user and does not pass down user information to MySQL or PostgreSQL connectors.


PostgreSQL and MySQL each support a wide variety of datatypes (PostgreSQL datatypes, MySQL datatypes). Many of these types are not supported in Presto. Table columns that are defined using an unsupported type are not visible to Presto users. These columns are not shown when describe table or select * SQL statements are executed.


CREATE TABLE (...) does not work, but CREATE TABLE AS SELECT does.


DROP TABLE is not supported.

Limited SQL push-down

Presto does not “push-down” aggregate calculations to PostgreSQL or MySQL. This means that when a user executes a simple query such as SELECT COUNT(*) FROM lineitem the entire table will be retrieved and the aggregate calculated by Presto. If the table is large or the network slow, this may take a very long time.

MySQL Catalogs

MySQL catalog names are mapped to Presto schema names.

19.2. Release 0.152.1-t.0.1

The following has been added to 0.152.1-t.0.1:

  • Fix issue “Hive table is corrupt. It is declared as being bucketed, but the files do not match the bucketing declaration. The number of files in the directory (1) does not match the declared.” by fixing support for Hive bucketed tables. See option hive.multi-file-bucketing.enabled in the Presto Hive connector documentation.
  • Fix issue “low must be less than or equal to high” that can occur with ORC and Character data.
  • Fix incorrect stream property derivations from GroupIdNode
  • Remove broken %w specifier for MySQL date functions
  • Optimize DictionaryBlock.copyPositions()

19.3. Release 0.152.1-t.0.2

The following has been added to 0.152.1-t.0.2:

  • Optimize execution order of Windowing functions to minimize the number of times data is repartitioned. For example:




If the execution order is as written in the query, it results in partitioning the data 3 times. If we rearrange to execute wfunc1 -> wfunc3 -> wfunc2 then data is only partitioned twice.

  • RPM to include installation of the Memory connector.

19.4. Release 0.152.1-t.0.3

The following has been added to 0.152.1-t.0.3:

  • Enable Presto 0.152.1-t to be used with QueryGrid 2.0
  • Allow empty partitions for clustered hive tables