> ## Documentation Index
> Fetch the complete documentation index at: https://cockroachlabs.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# SQL FAQs

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* To bulk-insert data into an existing table, batch multiple rows in one <InternalLink path="insert#insert-multiple-rows-into-an-existing-table">multi-row `INSERT`</InternalLink> statement and do not include the `INSERT` statements within a transaction. Experimentally determine the optimal batch size for your application by monitoring the performance for different batch sizes (10 rows, 100 rows, 1000 rows).

<Note>
  You can also use the <InternalLink path="import-into">`IMPORT INTO`</InternalLink> statement to bulk-insert CSV data into an existing table.
</Note>

* To bulk-insert data into a new table, the <InternalLink path="import">`IMPORT`</InternalLink> statement performs better than `INSERT`. `IMPORT` can also be used to <InternalLink version="molt" path="migration-overview">migrate data from other databases</InternalLink> like MySQL, Oracle, and PostgreSQL.

To auto-generate unique row identifiers, you can use the `gen_random_uuid()`, `uuid_v4()`, or `unique_rowid()` <InternalLink path="functions-and-operators#id-generation-functions">functions</InternalLink>.

To use the <InternalLink path="uuid">`UUID`</InternalLink> column with the `gen_random_uuid()` <InternalLink path="functions-and-operators#id-generation-functions">function</InternalLink> as the <InternalLink path="default-value">default value</InternalLink>:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
CREATE TABLE users (
    id UUID NOT NULL DEFAULT gen_random_uuid(),
    city STRING NOT NULL,
    name STRING NULL,
    address STRING NULL,
    credit_card STRING NULL,
    CONSTRAINT "primary" PRIMARY KEY (city ASC, id ASC),
    FAMILY "primary" (id, city, name, address, credit_card)
);
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
INSERT INTO users (name, city) VALUES ('Petee', 'new york'), ('Eric', 'seattle'), ('Dan', 'seattle');
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
SELECT * FROM users;
```

```text theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
                   id                  |   city   | name  | address | credit_card
+--------------------------------------+----------+-------+---------+-------------+
  cf8ee4e2-cd74-449a-b6e6-a0fb2017baa4 | new york | Petee | NULL    | NULL
  2382564e-702f-42d9-a139-b6df535ae00a | seattle  | Eric  | NULL    | NULL
  7d27e40b-263a-4891-b29b-d59135e55650 | seattle  | Dan   | NULL    | NULL
(3 rows)
```

Alternatively, you can use the <InternalLink path="bytes">`BYTES`</InternalLink> column with the `uuid_v4()` function as the default value:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
CREATE TABLE users2 (
    id BYTES DEFAULT uuid_v4(),
    city STRING NOT NULL,
    name STRING NULL,
    address STRING NULL,
    credit_card STRING NULL,
    CONSTRAINT "primary" PRIMARY KEY (city ASC, id ASC),
    FAMILY "primary" (id, city, name, address, credit_card)
);
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
INSERT INTO users2 (name, city) VALUES ('Anna', 'new york'), ('Jonah', 'seattle'), ('Terry', 'chicago');
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
SELECT * FROM users;
```

```text theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
                        id                       |   city   | name  | address | credit_card
+------------------------------------------------+----------+-------+---------+-------------+
  4\244\277\323/\261M\007\213\275*\0060\346\025z | chicago  | Terry | NULL    | NULL
  \273*t=u.F\010\274f/}\313\332\373a             | new york | Anna  | NULL    | NULL
  \004\\\364nP\024L)\252\364\222r$\274O0         | seattle  | Jonah | NULL    | NULL
(3 rows)
```

In either case, generated IDs will be 128-bit, sufficiently large to generate unique values. Once the table grows beyond a single key-value range's <InternalLink path="configure-replication-zones">default size</InternalLink>, new IDs will be scattered across all of the table's ranges and, therefore, likely across different nodes. This means that multiple nodes will share in the load.

This approach has the disadvantage of creating a primary key that may not be useful in a query directly, which can require a join with another table or a secondary index.

If it is important for generated IDs to be stored in the same key-value range, you can use an <InternalLink path="int">integer type</InternalLink> with the `unique_rowid()` <InternalLink path="functions-and-operators#id-generation-functions">function</InternalLink> as the default value, either explicitly or via the <InternalLink path="serial">`SERIAL` pseudo-type</InternalLink>:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
CREATE TABLE users3 (
    id INT DEFAULT unique_rowid(),
    city STRING NOT NULL,
    name STRING NULL,
    address STRING NULL,
    credit_card STRING NULL,
    CONSTRAINT "primary" PRIMARY KEY (city ASC, id ASC),
    FAMILY "primary" (id, city, name, address, credit_card)
);
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
INSERT INTO users3 (name, city) VALUES ('Blake', 'chicago'), ('Hannah', 'seattle'), ('Bobby', 'seattle');
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
SELECT * FROM users3;
```

```text theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
          id         |  city   |  name  | address | credit_card
+--------------------+---------+--------+---------+-------------+
  469048192112197633 | chicago | Blake  | NULL    | NULL
  469048192112263169 | seattle | Hannah | NULL    | NULL
  469048192112295937 | seattle | Bobby  | NULL    | NULL
(3 rows)
```

Upon insert or upsert, the `unique_rowid()` function generates a default value from the timestamp and ID of the node executing the insert. Such time-ordered values are likely to be globally unique except in cases where a very large number of IDs (100,000+) are generated per node per second. Also, there can be gaps and the order is not completely guaranteed.

To understand the differences between the `UUID` and `unique_rowid()` options, see the <InternalLink path="sql-faqs">SQL FAQs</InternalLink>. For further background on UUIDs, see [What is a UUID, and Why Should You Care?](https://www.cockroachlabs.com/blog/what-is-a-uuid).

Sequential numbers can be generated in CockroachDB using the `unique_rowid()` built-in function or using <InternalLink path="create-sequence">SQL sequences</InternalLink>. However, note the following considerations:

* Unless you need roughly-ordered numbers, use <InternalLink path="uuid">`UUID`</InternalLink> values instead. See the [previous FAQ](#how-do-i-auto-generate-unique-row-ids-in-cockroachdb) for details.
* <InternalLink path="create-sequence">Sequences</InternalLink> produce **unique** values. However, not all values are guaranteed to be produced (e.g., when a transaction is canceled after it consumes a value) and the values may be slightly reordered (e.g., when a transaction that consumes a lower sequence number commits after a transaction that consumes a higher number).
* For maximum performance, avoid using sequences or `unique_rowid()` to generate row IDs or indexed columns. Values generated in these ways are logically close to each other and can cause <InternalLink path="performance-best-practices-overview">contention</InternalLink> on a few data ranges during inserts. Instead, prefer <InternalLink path="uuid">`UUID`</InternalLink> identifiers.
* We <InternalLink path="schema-design-indexes#best-practices">discourage indexing on sequential keys</InternalLink>. If a table **must** be indexed on sequential keys, use <InternalLink path="hash-sharded-indexes">hash-sharded indexes</InternalLink>. Hash-sharded indexes distribute sequential traffic uniformly across ranges, eliminating single-range <InternalLink path="performance-best-practices-overview#hot-spots">hot spots</InternalLink> and improving write performance on sequentially-keyed indexes at a small cost to read performance.

| Property                             | UUID generated with `uuid\_v4()`  | INT generated with `unique\_rowid()`          | Sequences                                                                                              |
| ------------------------------------ | --------------------------------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------ |
| Size                                 | 16 bytes                          | 8 bytes                                       | 1 to 8 bytes                                                                                           |
| Ordering properties                  | Unordered                         | Highly time-ordered                           | Highly time-ordered                                                                                    |
| Performance cost at generation       | Small, scalable                   | Small, scalable                               | Variable, can cause <InternalLink path="performance-best-practices-overview">contention</InternalLink> |
| Value distribution                   | Uniformly distributed (128 bits)  | Contains time and space (node ID) components  | Dense, small values                                                                                    |
| Data locality                        | Maximally distributed             | Values generated close in time are co-located | Highly local                                                                                           |
| `INSERT` latency when used as key    | Small, insensitive to concurrency | Small, but increases with concurrent INSERTs  | Higher                                                                                                 |
| `INSERT` throughput when used as key | Highest                           | Limited by max throughput on 1 node           | Limited by max throughput on 1 node                                                                    |
| Read throughput when used as key     | Highest (maximal parallelism)     | Limited                                       | Limited                                                                                                |

Most use cases that ask for a strong time-based write ordering can be solved with other, more distribution-friendly solutions instead. For example, CockroachDB's [time travel queries (`AS OF SYSTEM
TIME`)](https://www.cockroachlabs.com/blog/time-travel-queries-select-witty_subtitle-the_future) support the following:

* Paginating through all the changes to a table or dataset
* Determining the order of changes to data over time
* Determining the state of data at some point in the past
* Determining the changes to data between two points of time

Consider also that the values generated by `unique_rowid()`, described in the previous FAQ entries, also provide an approximate time ordering.

However, if your application absolutely requires strong time-based write ordering, it is possible to create a strictly monotonic counter in CockroachDB that increases over time as follows:

* Initially: `CREATE TABLE cnt(val INT PRIMARY KEY); INSERT INTO cnt(val) VALUES(1);`
* In each transaction: `INSERT INTO cnt(val) SELECT max(val)+1 FROM cnt RETURNING val;`

This will cause <InternalLink path="insert">`INSERT`</InternalLink> transactions to conflict with each other and effectively force the transactions to commit one at a time throughout the cluster, which in turn guarantees the values generated in this way are strictly increasing over time without gaps. The caveat is that performance is severely limited as a result.

If you find yourself interested in this problem, please <InternalLink path="support-resources">contact us</InternalLink> and describe your situation. We would be glad to help you find alternative solutions and possibly extend CockroachDB to better match your needs.

There’s no function in CockroachDB for returning last inserted values, but you can use the <InternalLink path="insert#insert-and-return-values">`RETURNING` clause</InternalLink> of the `INSERT` statement.

For example, this is how you’d use `RETURNING` to return a value auto-generated via `unique_rowid()` or <InternalLink path="serial">`SERIAL`</InternalLink>:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> CREATE TABLE users (id INT DEFAULT unique_rowid(), name STRING);
```

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> INSERT INTO users (name) VALUES ('mike') RETURNING id;
```

Transaction contention occurs when transactions issued from multiple clients at the same time operate on the same data. This can cause transactions to wait on each other and decrease performance, like when many people try to check out with the same cashier at a store.

For more information about contention, see <InternalLink path="performance-best-practices-overview#transaction-contention">Transaction Contention</InternalLink>.

<InternalLink path="joins">CockroachDB supports SQL joins</InternalLink>.

Yes, the <InternalLink path="jsonb">`JSONB`</InternalLink> data type is supported.

To see which indexes CockroachDB is using for a given query, you can use the <InternalLink path="explain">`EXPLAIN`</InternalLink> statement, which will print out the query plan, including any indexes that are being used:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> EXPLAIN SELECT col1 FROM tbl1;
```

If you'd like to tell the query planner which index to use, you can do so via some <InternalLink path="table-expressions#force-index-selection">special syntax for index hints</InternalLink>:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> SELECT col1 FROM tbl1@idx1;
```

You can enable the CockroachDB <InternalLink path="logging-overview#logging-channels">logging channels</InternalLink> that record SQL events.

Yes. For more details, see <InternalLink path="uuid">`UUID`</InternalLink>.

When an <InternalLink path="order-by">`ORDER BY`</InternalLink> clause is not used in a query, rows are processed or returned in a non-deterministic order. "Non-deterministic" means that the actual order can depend on the logical plan, the order of data on disk, the topology of the CockroachDB cluster, and is generally variable over time.

In CockroachDB, all `INT`s are represented with 64 bits of precision, but JavaScript numbers only have 53 bits of precision. This means that large integers stored in CockroachDB are not exactly representable as JavaScript numbers. For example, JavaScript will round the integer `235191684988928001` to the nearest representable value, `235191684988928000`. Notice that the last digit is different. This is particularly problematic when using the `unique_rowid()` <InternalLink path="functions-and-operators">function</InternalLink>, since `unique_rowid()` nearly always returns integers that require more than 53 bits of precision to represent.

To avoid this loss of precision, Node's [`pg` driver](https://github.com/brianc/node-postgres) will, by default, return all CockroachDB `INT`s as strings.

```javascript theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
// Schema: CREATE TABLE users (id INT DEFAULT unique_rowid(), name STRING);
pgClient.query("SELECT id FROM users WHERE name = 'Roach' LIMIT 1", function(err, res) {
  var idString = res.rows[0].id;
  // idString === '235191684988928001'
  // typeof idString === 'string'
});
```

To perform another query using the value of `idString`, you can simply use `idString` directly, even where an `INT` type is expected. The string will automatically be coerced into a CockroachDB `INT`.

```javascript theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
pgClient.query("UPDATE users SET name = 'Ms. Roach' WHERE id = $1", [idString], function(err, res) {
  // All should be well!
});
```

If you instead need to perform arithmetic on `INT`s in JavaScript, you will need to use a big integer library like [Long.js](https://www.npmjs.com/package/long). Do *not* use the built-in `parseInt` function.

```javascript theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
parseInt(idString, 10) + 1; // WRONG: returns 235191684988928000
require('long').fromString(idString).add(1).toString(); // GOOD: returns '235191684988928002'
```

CockroachDB is a distributed SQL database built on a transactional and strongly-consistent key-value store. Although it is not possible to access the key-value store directly, you can mirror direct access using a "simple" table of two columns, with one set as the primary key:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> CREATE TABLE kv (k INT PRIMARY KEY, v BYTES);
```

When such a "simple" table has no indexes or foreign keys, <InternalLink path="insert">`INSERT`</InternalLink>/<InternalLink path="upsert">`UPSERT`</InternalLink>/<InternalLink path="update">`UPDATE`</InternalLink>/<InternalLink path="delete">`DELETE`</InternalLink> statements translate to key-value operations with minimal overhead (single digit percent slowdowns). For example, the following `UPSERT` to add or replace a row in the table would translate into a single key-value Put operation:

```sql theme={"theme":{"light":"catppuccin-mocha","dark":"catppuccin-mocha"}}
> UPSERT INTO kv VALUES (1, b'hello')
```

This SQL table approach also offers you a well-defined query language, a known transaction model, and the flexibility to add more columns to the table if the need arises.

Yes. For more information, see <InternalLink path="full-text-search">Full-Text Search</InternalLink>.

Depending on your use case, you may prefer to use <InternalLink path="trigram-indexes">trigram indexes</InternalLink> to do fuzzy string matching and pattern matching. For more information about use cases for trigram indexes that could make having full-text search unnecessary, see the 2022 blog post [Use cases for trigram indexes (when not to use Full Text Search)](https://www.cockroachlabs.com/blog/use-cases-trigram-indexes).

## See also

* <InternalLink path="frequently-asked-questions">Product FAQs</InternalLink>
* <InternalLink path="operational-faqs">Operational FAQS</InternalLink>