INSERT

Updates a table by inserting one or more rows into the table. The values inserted into each column in the table can be explicitly-specified or the results of a query.

See also:

INSERT (multi-table)

Syntax

INSERT [ OVERWRITE ] INTO <target_table> [ ( <target_col_name> [ , ... ] ) ]
       {
           VALUES ( { <value> | DEFAULT | NULL } [ , ... ] ) [ , ( ... ) ]
         | <query>
       }

Required parameters

target_table

Specifies the target table into which to insert rows.

VALUES ( value | DEFAULT | NULL [ , ... ] )  [ , ( ... ) ]

Specifies one or more values to insert into the corresponding columns in the target table.

In a VALUES clause, you can specify the following:

  • value: Inserts the explicitly-specified value. The value can be a literal or an expression that evaluates to a single value.

  • DEFAULT: Inserts the default value for the corresponding column in the target table.

  • NULL: Inserts a NULL value.

Each value in the clause must be separated by a comma.

You can insert multiple rows by specifying additional sets of values in the clause. For more information, see the Usage notes and the Examples.

query

Specify a query statement that returns values to be inserted into the corresponding columns. This allows you to insert rows into a target table from one or more source tables.

Optional parameters

OVERWRITE

Specifies that the target table should be truncated before inserting the values into the table. Note that specifying this option does not affect the access control privileges on the table.

INSERT statements with OVERWRITE can be processed within the scope of the current transaction, which avoids DDL statements that commit a transaction, such as:

DROP TABLE t;
CREATE TABLE t AS SELECT * FROM ... ;

Default: No value (the target table is not truncated before performing the inserts).

( target_col_name [ , ... ] )

Specifies one or more columns in the target table into which the corresponding values are inserted. The number of target columns specified must match the number of specified values or columns (if the values are the results of a query) in the VALUES clause.

Default: No value (all the columns in the target table are updated).

Usage notes

  • Using a single INSERT command, you can insert multiple rows into a table by specifying additional sets of values separated by commas in the VALUES clause.

    For example, the following clause would insert 3 rows in a 3-column table, with values 1, 2, and 3 in the first two rows and values 2, 3, and 4 in the third row:

    VALUES ( 1, 2, 3 ) ,
       ( 1, 2, 3 ) ,
       ( 2, 3, 4 )

  • To use the OVERWRITE option on INSERT, you must use a role that has DELETE privilege on the table because OVERWRITE will delete the existing records in the table.

  • Some types of expressions can’t be specified in the VALUES clause, including the following expressions:

    • Subqueries

      For example:

      ... VALUES (SELECT id FROM other_table)

    • Values of the semi-structured or structured data type.

      For example:

      ... VALUES (ARRAY_CONSTRUCT(1, 2, 3))

    • Window functions

      For example:

      ... VALUES (ROW_NUMBER() OVER (...))

    • Aggregate functions

      For example:

      ... VALUES (SUM(x))

    As an alternative to the VALUES clause, specify the expression in a query clause. For example, you can replace the following expression:

    INSERT INTO table1 (ID, varchar1, variant1)
    VALUES (4, 'Fourier', PARSE_JSON('{ "key1": "value1", "key2": "value2" }'));

    with this expression:

    INSERT INTO table1 (ID, varchar1, variant1)
    SELECT 4, 'Fourier', PARSE_JSON('{ "key1": "value1", "key2": "value2" }');

  • The VALUES clause is limited to 200,000 rows. This limit applies to a single INSERT INTO … VALUES statement and a single INSERT INTO … SELECT … FROM VALUES statement. Consider using the COPY INTO <table> command to perform a bulk data load. For more information about using the VALUES clause in a SELECT statement, see VALUES.

  • For information about inserting data into hybrid tables, see Loading data.

Examples

The following examples use the INSERT command.

Single row insert using a query

Convert three string values to dates or timestamps and insert them into a single row in the mytable table:

CREATE OR REPLACE TABLE mytable (
  col1 DATE,
  col2 TIMESTAMP_NTZ,
  col3 TIMESTAMP_NTZ);

DESC TABLE mytable;

+------+------------------+--------+-------+---------+-------------+------------+-------+------------+---------+-------------+----------------+
| name | type             | kind   | null? | default | primary key | unique key | check | expression | comment | policy name | privacy domain |
|------+------------------+--------+-------+---------+-------------+------------+-------+------------+---------+-------------+----------------|
| COL1 | DATE             | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    | NULL        | NULL           |
| COL2 | TIMESTAMP_NTZ(9) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    | NULL        | NULL           |
| COL3 | TIMESTAMP_NTZ(9) | COLUMN | Y     | NULL    | N           | N          | NULL  | NULL       | NULL    | NULL        | NULL           |
+------+------------------+--------+-------+---------+-------------+------------+-------+------------+---------+-------------+----------------+

INSERT INTO mytable
  SELECT
    TO_DATE('2013-05-08T23:39:20.123'),
    TO_TIMESTAMP('2013-05-08T23:39:20.123'),
    TO_TIMESTAMP('2013-05-08T23:39:20.123');

SELECT * FROM mytable;

+------------+-------------------------+-------------------------+
| COL1       | COL2                    | COL3                    |
|------------+-------------------------+-------------------------|
| 2013-05-08 | 2013-05-08 23:39:20.123 | 2013-05-08 23:39:20.123 |
+------------+-------------------------+-------------------------+

Similar to previous example, but specify to update only the first and third columns in the table:

INSERT INTO mytable (col1, col3)
  SELECT
    TO_DATE('2013-05-08T23:39:20.123'),
    TO_TIMESTAMP('2013-05-08T23:39:20.123');

SELECT * FROM mytable;

+------------+-------------------------+-------------------------+
| COL1       | COL2                    | COL3                    |
|------------+-------------------------+-------------------------|
| 2013-05-08 | 2013-05-08 23:39:20.123 | 2013-05-08 23:39:20.123 |
| 2013-05-08 | NULL                    | 2013-05-08 23:39:20.123 |
+------------+-------------------------+-------------------------+

Multi-row insert using explicitly-specified values

Create the employees table and insert four rows of data into it by providing sets of values in a comma-separated list in the VALUES clause:

CREATE TABLE employees (
  first_name VARCHAR,
  last_name VARCHAR,
  workphone VARCHAR,
  city VARCHAR,
  postal_code VARCHAR);

INSERT INTO employees
  VALUES
    ('May', 'Franklin', '1-650-249-5198', 'San Francisco', 94115),
    ('Gillian', 'Patterson', '1-650-859-3954', 'San Francisco', 94115),
    ('Lysandra', 'Reeves', '1-212-759-3751', 'New York', 10018),
    ('Michael', 'Arnett', '1-650-230-8467', 'San Francisco', 94116);

SELECT * FROM employees;

+------------+-----------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+-----------+----------------+---------------+-------------|
| May        | Franklin  | 1-650-249-5198 | San Francisco | 94115       |
| Gillian    | Patterson | 1-650-859-3954 | San Francisco | 94115       |
| Lysandra   | Reeves    | 1-212-759-3751 | New York      | 10018       |
| Michael    | Arnett    | 1-650-230-8467 | San Francisco | 94116       |
+------------+-----------+----------------+---------------+-------------+

In multi-row inserts, make sure that the data types of the inserted values are consistent across the rows because the data type of the first row is used as a guide. Create a table and insert two rows:

CREATE OR REPLACE TABLE demo_insert_type_mismatch (v VARCHAR);

The first insert works as expected:

INSERT INTO demo_insert_type_mismatch (v) VALUES
  ('three'),
  ('four');

+-------------------------+
| number of rows inserted |
|-------------------------|
|                       2 |
+-------------------------+

The second insert fails because the data type of the value in the second row ('d') is a string, which is different from the numeric data type of the value in the first row (3). The insert fails even though both values can be coerced to VARCHAR, which is the data type of the column in the table. The insert fails even though the data type of the value 'd' is the same as the data type of column v:

INSERT INTO demo_insert_type_mismatch (v) VALUES
  (3),
  ('d');

100038 (22018): DML operation to table DEMO_INSERT_TYPE_MISMATCH failed on column V with error: Numeric value 'd' is not recognized

When the data types are consistent across the rows, the insert succeeds, and both numeric values are coerced to the VARCHAR data type:

INSERT INTO demo_insert_type_mismatch (v) VALUES
  (3),
  (4);

+-------------------------+
| number of rows inserted |
|-------------------------|
|                       2 |
+-------------------------+

Multi-row insert using query

Insert multiple rows of data from the contractors table into the employees table:

  • Select only those rows where the worknum column contains area code 650.

  • Insert a NULL value in the city column.

SELECT * FROM employees;

+------------+-----------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+-----------+----------------+---------------+-------------|
| May        | Franklin  | 1-650-249-5198 | San Francisco | 94115       |
| Gillian    | Patterson | 1-650-859-3954 | San Francisco | 94115       |
| Lysandra   | Reeves    | 1-212-759-3751 | New York      | 10018       |
| Michael    | Arnett    | 1-650-230-8467 | San Francisco | 94116       |
+------------+-----------+----------------+---------------+-------------+

CREATE TABLE contractors (
  contractor_first VARCHAR,
  contractor_last VARCHAR,
  worknum VARCHAR,
  city VARCHAR,
  zip_code VARCHAR);

INSERT INTO contractors
  VALUES
    ('Bradley', 'Greenbloom', '1-650-445-0676', 'San Francisco', 94110),
    ('Cole', 'Simpson', '1-212-285-8904', 'New York', 10001),
    ('Laurel', 'Slater', '1-650-633-4495', 'San Francisco', 94115);

SELECT * FROM contractors;

+------------------+-----------------+----------------+---------------+----------+
| CONTRACTOR_FIRST | CONTRACTOR_LAST | WORKNUM        | CITY          | ZIP_CODE |
|------------------+-----------------+----------------+---------------+----------|
| Bradley          | Greenbloom      | 1-650-445-0676 | San Francisco | 94110    |
| Cole             | Simpson         | 1-212-285-8904 | New York      | 10001    |
| Laurel           | Slater          | 1-650-633-4495 | San Francisco | 94115    |
+------------------+-----------------+----------------+---------------+----------+

INSERT INTO employees(first_name, last_name, workphone, city, postal_code)
  SELECT contractor_first, contractor_last, worknum, NULL, zip_code
    FROM contractors
    WHERE CONTAINS(worknum,'650');

SELECT * FROM employees;

+------------+------------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME  | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+------------+----------------+---------------+-------------|
| May        | Franklin   | 1-650-249-5198 | San Francisco | 94115       |
| Gillian    | Patterson  | 1-650-859-3954 | San Francisco | 94115       |
| Lysandra   | Reeves     | 1-212-759-3751 | New York      | 10018       |
| Michael    | Arnett     | 1-650-230-8467 | San Francisco | 94116       |
| Bradley    | Greenbloom | 1-650-445-0676 | NULL          | 94110       |
| Laurel     | Slater     | 1-650-633-4495 | NULL          | 94115       |
+------------+------------+----------------+---------------+-------------+

Insert multiple rows of data from the contractors table into the employees table using a common table expression:

INSERT INTO employees (first_name, last_name, workphone, city, postal_code)
  WITH cte AS
    (SELECT contractor_first AS first_name,
            contractor_last AS last_name,
            worknum AS workphone,
            city,
            zip_code AS postal_code
       FROM contractors)
  SELECT first_name, last_name, workphone, city, postal_code
    FROM cte;

Insert columns from two tables (emp_addr, emp_ph) into a third table (emp) using an INNER JOIN on the id column in the source tables:

INSERT INTO emp (id, first_name, last_name, city, postal_code, ph)
  SELECT a.id, a.first_name, a.last_name, a.city, a.postal_code, b.ph
    FROM emp_addr a
    INNER JOIN emp_ph b ON a.id = b.id;

Multi-row insert for JSON data

Insert two JSON objects into a VARIANT column in a table:

CREATE TABLE prospects (column1 VARIANT);

INSERT INTO prospects
  SELECT PARSE_JSON(column1)
  FROM VALUES
  ('{
    "_id": "57a37f7d9e2b478c2d8a608b",
    "name": {
      "first": "Lydia",
      "last": "Williamson"
    },
    "company": "Miralinz",
    "email": "lydia.williamson@miralinz.info",
    "phone": "+1 (914) 486-2525",
    "address": "268 Havens Place, Dunbar, Rhode Island, 02801"
  }')
  , ('{
    "_id": "57a37f7d622a2b1f90698c01",
    "name": {
      "first": "Denise",
      "last": "Holloway"
    },
    "company": "DIGIGEN",
    "email": "denise.holloway@digigen.net",
    "phone": "+1 (979) 587-3021",
    "address": "441 Dover Street, Ada, New Mexico, 87105"
  }');

Insert using OVERWRITE

This example uses INSERT with OVERWRITE to rebuild the sf_employees table from employees after new records were added to the employees table.

Here is the initial data for both tables:

SELECT * FROM employees;

+------------+-----------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+-----------+----------------+---------------+-------------|
| May        | Franklin  | 1-650-111-1111 | San Francisco | 94115       |
| Gillian    | Patterson | 1-650-222-2222 | San Francisco | 94115       |
| Lysandra   | Reeves    | 1-212-222-2222 | New York      | 10018       |
| Michael    | Arnett    | 1-650-333-3333 | San Francisco | 94116       |
+------------+-----------+----------------+---------------+-------------+

SELECT * FROM sf_employees;

+------------+-----------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+-----------+----------------+---------------+-------------|
| Mary       | Smith     | 1-650-999-9999 | San Francisco | 94115       |
+------------+-----------+----------------+---------------+-------------+

This statement inserts rows into the sf_employees table using the OVERWRITE clause:

INSERT OVERWRITE INTO sf_employees
  SELECT * FROM employees
  WHERE city = 'San Francisco';

Because the INSERT used the OVERWRITE clause, the old rows from sf_employees are gone:

SELECT * FROM sf_employees;

+------------+-----------+----------------+---------------+-------------+
| FIRST_NAME | LAST_NAME | WORKPHONE      | CITY          | POSTAL_CODE |
|------------+-----------+----------------+---------------+-------------|
| May        | Franklin  | 1-650-111-1111 | San Francisco | 94115       |
| Gillian    | Patterson | 1-650-222-2222 | San Francisco | 94115       |
| Michael    | Arnett    | 1-650-333-3333 | San Francisco | 94116       |
+------------+-----------+----------------+---------------+-------------+

Write to a v3 Apache Iceberg™ table

The following example inserts a row into an Apache Iceberg™ table that conforms to v3 of the Apache Iceberg™ table specification:

INSERT INTO my_v3_iceberg_table (id, payload) VALUES (1, PARSE_JSON('{"name": "Alice", "age": 30}'));