DDL - Tables

Nomenclature Constraints

Table names must use the NAME format, described in regex notation as:

[A-Za-z_][A-Za-z0-9\$_]*

CREATE TABLE

CREATE TABLE [IF NOT EXISTS] <table>
  (<column> <type> [NOT NULL] [ENCODING <encodingSpec>],
  [SHARD KEY (<column>)],
  [SHARED DICTIONARY (<column>) REFERENCES <table>(<column>)], ...)
  [WITH (<property> = value, ...)];

Create a table named <table> specifying <columns> and table properties. Table and column names cannot include quotes, spaces, or special characters.

CREATE TABLE IF NOT EXISTS tweets (
   tweet_id BIGINT NOT NULL,
   tweet_time TIMESTAMP NOT NULL ENCODING FIXED(32),
   lat FLOAT,
   lon FLOAT,
   sender_id BIGINT NOT NULL,
   sender_name TEXT NOT NULL ENCODING DICT,
   location TEXT ENCODING  DICT,
   source TEXT ENCODING DICT,
   reply_to_user_id BIGINT,
   reply_to_tweet_id BIGINT,
   lang TEXT ENCODING  DICT,
   followers INT,
   followees INT,
   tweet_count INT,
   join_time TIMESTAMP ENCODING  FIXED(32),
   tweet_text TEXT,
   state TEXT ENCODING  DICT,
   county TEXT ENCODING DICT,
   place_name TEXT,
   state_abbr TEXT ENCODING DICT,
   county_state TEXT ENCODING DICT,
   origin TEXT ENCODING DICT,
   phone_numbers bigint);

CREATE TABLE  customers(
   accountId text,
   name text,
   SHARD KEY (accountId))
  WITH (shard_count = 4);

CREATE TABLE transactions(
   accountId text,
   action text,
   SHARD KEY (accountId),
   SHARED DICTIONARY (accountId) REFERENCES customers(accountId))
  WITH (shard_count = 4);

CREATE TABLE AS SELECT

CREATE TABLE <newTableName> AS (<SELECT statement>) [WITH (<property> = value, ...)];

Create a table with the specified columns, copying any data that meet SELECT statement criteria.

Examples

Create the table newTable. Populate the table with all information from the table oldTable, effectively creating a duplicate of the original table.

CREATE TABLE newTable AS (SELECT * FROM oldTable);

Create a table named trousers. Populate it with data from the columns name, waist, and inseam from the table wardrobe.

CREATE TABLE trousers AS (SELECT name, waist, inseam FROM wardrobe);

Create a table named cosmos. Populate it with data from the columns star and planet from the table universe where planet has the class M.

CREATE TABLE cosmos AS (SELECT star, planet FROM universe WHERE class='M');

ALTER TABLE

ALTER TABLE <table> RENAME TO <table>;
ALTER TABLE <table> RENAME COLUMN <column> TO <column>;
ALTER TABLE <table> ADD [COLUMN] <column> <type> [NOT NULL] [ENCODING <encodingSpec>]
ALTER TABLE <table> ADD (<column> <type> [NOT NULL] [ENCODING <encodingSpec>], ...)

Examples

Rename the table tweets to retweets.

ALTER TABLE tweets RENAME TO retweets;

Rename the column source to device in the table retweets.

ALTER TABLE retweets RENAME COLUMN source TO device;

Add the column lang to the table tweets using a TEXT ENCODING DICTIONARY.

ALTER TABLE tweets ADD COLUMN lang TEXT ENCODING DICT;

Add the columns lang and encode to the table tweets using a TEXT ENCODING DICTIONARY for each.

ALTER TABLE tweets ADD (lang TEXT ENCODING DICT, encode TEXT ENCODING DICT);

DROP TABLE

DROP TABLE [IF EXISTS] <table>;

Deletes the table structure, all data from the table, and any dictionary content unless it is a shared dictionary. (See the note regarding disk space reclamation.)

Example

DROP TABLE IF EXISTS tweets;

TRUNCATE TABLE

TRUNCATE TABLE <table>;

Use the TRUNCATE TABLE statement to remove all rows from a table without deleting the table structure.

This releases table on-disk and memory storage and removes dictionary content unless it is a shared dictionary. (See the note regarding disk space reclamation.)

Removing rows is more efficient than using DROP TABLE. Dropping followed by recreating the table invalidates dependent objects of the table requiring you to regrant object privileges. Truncating has none of these effects.

Example

TRUNCATE TABLE tweets;

OPTIMIZE TABLE

OPTIMIZE TABLE [<table>] [WITH (VACUUM='true')]

Use this statement to remove rows from storage that have been marked as deleted via DELETE statements.

When run without the vacuum option, the column-level metadata is recomputed for each column in the specified table. OmniSci Core makes heavy use of metadata to optimize query plans, so optimizing table metadata can increase query performance after metadata widening operations such as updates or deletes. OmniSci Core does not narrow metadata during an update or delete — metadata is only widened to cover a new range.

When run with the vacuum option, it removes any rows marked "deleted" from the data stored on disk. Vacuum is a checkpointing operation, so new copies of any vacuum records are deleted. OmniSci Core currently does not remove old (pre-checkpoint) fragments after vacuuming, so you might notice your data directory growing.

VALIDATE CLUSTER

VALIDATE CLUSTER [WITH (REPAIR_TYPE = ['NONE' | 'REMOVE'])];

Perform checks and report discovered issues on a running OmniSci cluster. Compare metadata between the aggregator and leaves to verify that the logical components between the processes are identical.

Examples

If VALIDATE CLUSTER detects issues, it returns a report similar to the following:

mapd@thing3 ~]$ /mnt/gluster/dist_mapd/mapd-sw2/bin/mapdql -p HyperInteractive
User mapd connected to database mapd
omnisql> validate cluster;
Result
 Node          Table Count 
 ===========   =========== 
 Aggregator     1116
 Leaf 0         1114
 Leaf 1         1114
No matching table on Leaf 0 for Table cities_dtl_POINTS table id 56
No matching table on Leaf 1 for Table cities_dtl_POINTS table id 56
No matching table on Leaf 0 for Table cities_dtl table id 80
No matching table on Leaf 1 for Table cities_dtl table id 80
Table details don't match on Leaf 0 for Table view_geo table id 95
Table details don't match on Leaf 1 for Table view_geo table id 95

If no issues are detected, it will report as follows:

Cluster OK

You can include the WITH(REPAIR_TYPE) argument. (REPAIR_TYPE='NONE') is the same as running the command with no argument. (REPAIR_TYPE='REMOVE') removes any leaf objects that have issues. For example:

VALIDATE CLUSTER WITH (REPAIR_TYPE = 'REMOVE');