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Lightweight Transactions

New in version 3.2: Scylla Open Source (experimental)

Changed in version 4.0: Scylla Open Source (production ready)

In releases prior to Scylla 4.0 this feature is an experimental feature, to use it you must enable the experimental status.

There are cases when it is necessary to modify data based on its current state: that is, to perform an update that is executed only if a row does not exist or contains a certain value. LWTs provide this functionality by only allowing changes to data to occur if the condition provided evaluates as true. The conditional statements provide linearizable semantics thus allowing data to remain consistent.

A basic rule of thumb is that any statement with an IF clause is a conditional statement. A batch that has at least one conditional statement is a conditional batch. Conditional statements and conditional batches are executed atomically, as a Lightweight Transaction (LWT) For example:

UPDATE employees SET join_date = '2018-05-19' WHERE
   firstname = 'John' AND lastname = 'Doe'
   IF join_date != null;

The example above updates the employee John Doe’s start date if John Doe has a record in the employees table.

The IF clause

Creating a conditional statement with an IF clause can include a query of individual cells and or collection elements. It can use IN clauses or comparison operators, such as <, >, >=, <=, ==, and !=. The important part to keep in mind is that in order to initiate the transaction, the condition must evaluate to true and if there are several different elements in the conditional statement, each part must evaluate to true. If any part evaluates to false the transaction does not complete.

The IF condition can be created from any of the following CQL components: IF EXISTS, IF NOT EXISTS, or one or more predicates on the existing row.

Scylla Paxos

The statements with an IF clause use a different write path, employing the Paxos consensus algorithm (see figure) to ensure linearizability of the execution history.

../../_images/lwt.png

In Paxos, in order to persist a change a coordinator first must create a unique time-based identifier, called a ballot, and send it to replicas. Upon receiving a ballot, replicas respond with a promise to accept a change associated with it.

A replica refuses to promise a ballot if it has already promised a newer one – this locks out concurrent modification attempts and allows the coordinator to proceed with reading and updating a row without interference. The state of the protocol is persisted in system.paxos table, which is local to each replica.

Unlike Cassandra, Scylla piggy-backs the old version of the row on response to “Prepare” request, so reading a row doesn’t require a separate message exchange.

Once the coordinator gets a majority of promises from replicas, it evaluates the IF conditions, and if the result is true, sends an updated mutation to replicas. Replicas store the new row in system.paxos and acknowledge accepting it.

Having a majority of replicas accept the row satisfies the “quorum intersection” rule: as long as at least a majority of nodes are up, each conceivable new quorum contains at least one node which accepted the previous row and is thus aware of the change.

After the coordinator has received the majority of accepts, Paxos protocol round is complete, and it is safe to update the base table with the new row. This is done in “Learn” round.

If the base table update is successful, the coordinator responds to the client. It’s also safe to prune the state of the protocol from system.paxos.

The size of the quorum impacts how many acknowledgements the coordinator must get before proceeding to the next round or responding to the client. For Prepare and Accept, it is configured with SERIAL CONSISTENCY setting. For Learn, Scylla’s eventual CONSISTENCY is used. Pruning is done in the background.

Key differences between Scylla and Cassandra Paxos implementations are in collapsing prepare and read actions into a single round, and also introducing an extra asynchronous “prune” round, which keeps system.paxos table small and thus reduces write amplification when it’s compacted.

Note

The default TTL on records in system.paxos table is 3 hours. This means that all of the ballots are kept for at least 3 hours. Alternatively, you can change this value by altering the system.paxos table and setting the gc_grace_seconds parameter to a higher value. The higher of the two settings (3 hours or gc_grace_seconds) is the one which is used for the TTL on the system.paxos table.

Batch statements

BATCH statements may contain one or more conditional statements and as such, these batches are called conditional batches. The entire conditional batch has an isolated view of the database and is executed using all-or-nothing principle. In many ways, conditional batches are similar to ACID transactions in relational databases, with the exception that a batch is executed only if all conditions in all statements are true, if not it does nothing.

Reading with Paxos

For queries against a single partition, it’s possible to use Paxos for reading. Paxos reads are useful if it’s necessary to retrieve the most up to date version of a row: a simple QUORUM read may not see a value that is currently being updated by a conditional write. In order to ensure a read is serial, set CONSISTENCY to SERIAL in cqlsh or prepared statement properties.

SELECT * FROM employees WHERE firstname = 'John' AND lastname = 'Doe'

CQL examples with lightweight transactions

Add values to a table with LWT

Suppose you have a company which advertises movies playing in the cinema. The application allows customers to search for a movie, and to buy a ticket. You can use lightweight transactions for any of the following activities:

  • Change the existing movie’s offering by adding a new movie screening time (and not changing the other data for the movie)

  • Remove a movie which is no longer playing

  • Add a new movie to the New Releases page (as long as it isn’t already there)

  1. Create a Keyspace

    CREATE KEYSPACE movies
       WITH replication =
       {'class': 'NetworkTopologyStrategy', 'replication_factor' : 3};
    
  2. Create a table

    CREATE TABLE movies.nowshowing (
        movie TEXT,
        director TEXT static,
        main_actor TEXT static,
        released DATE static,
        location TEXT,
        run_day TEXT,
        run_time TIME,
        theater TEXT,
        PRIMARY KEY (movie, location, run_day, run_time)
    );
    
  3. Insert values into the table using LWT:

    INSERT INTO movies.nowshowing (movie, director, main_actor, released)
    VALUES ('Sonic the Hedgehog', 'Jeff Fowler', 'Ben Schwartz', '2020-14-02')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, director, main_actor, released)
    VALUES ('Invisible Man', 'Leigh Whannell', 'Elisabeth Moss', '2020-28-02')
    IF NOT EXISTS;
    
  4. Show the current table

    SELECT * FROM movies.nowshowing;
    
    
     movie              | location | run_day | run_time | director       | main_actor     | released   | theater
    --------------------+----------+---------+----------+----------------+----------------+------------+---------
     Sonic the Hedgehog |     null |    null |     null |    Jeff Fowler |   Ben Schwartz | 2021-02-02 |    null
          Invisible Man |     null |    null |     null | Leigh Whannell | Elisabeth Moss | 2022-04-06 |    null
    
    (2 rows)
    
  5. Add more information to the table

    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Sonic the Hedgehog', 'Times Square', 'AMC Empire 25', 'Saturday', '21:00:00')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Sonic the Hedgehog', 'Penn Station', 'AMC 34th Street 14', 'Sunday', '14:00:00')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Sonic the Hedgehog', 'Times Square', 'AMC Empire 25', 'Saturday', '14:00:00')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Sonic the Hedgehog', 'Penn Station', 'AMC 34th Street 14', 'Sunday', '21:00:00')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Invisible Man', 'Penn Station', 'AMC 34th Street 14', 'Sunday', '22:00:00')
    IF NOT EXISTS;
    
    INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
    VALUES ('Invisible Man', 'Times Square', 'AMC Empire 25', 'Saturday', '22:00:00')
    IF NOT EXISTS;
    
  6. Show the current table

    SELECT * FROM movies.nowshowing;
    
    
     movie              | location     | run_day  | run_time           | director       | main_actor     | released   | theater
    --------------------+--------------+----------+--------------------+----------------+----------------+------------+--------------------
     Sonic the Hedgehog | Penn Station |   Sunday | 14:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 | AMC 34th Street 14
     Sonic the Hedgehog | Penn Station |   Sunday | 21:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 | AMC 34th Street 14
     Sonic the Hedgehog | Times Square | Saturday | 14:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 |      AMC Empire 25
     Sonic the Hedgehog | Times Square | Saturday | 21:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 |      AMC Empire 25
          Invisible Man | Penn Station |   Sunday | 18:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 | AMC 34th Street 14
          Invisible Man | Penn Station |   Sunday | 22:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 | AMC 34th Street 14
          Invisible Man | Times Square |   Friday | 21:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 |      AMC Empire 25
          Invisible Man | Times Square | Saturday | 22:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 |      AMC Empire 25
    
    (8 rows)
    

Update a table using a LWT

In this example the Times Square AMC theater needs to change the theater name from AMC Empire 25 to AMC Empire. It can be done using a conditional UPDATE, as shown here:

  1. Update the table:

    UPDATE movies.nowshowing SET theater = 'AMC Empire'
    WHERE location = 'Times Square'
      AND run_day = 'Saturday' AND run_time ='14:00:00'
      AND Movie = 'Sonic the Hedgehog'
    IF EXISTS;
    
     [applied] | movie              | location     | run_day  | run_time           | director    | main_actor   | released   | theater
    -----------+--------------------+--------------+----------+--------------------+-------------+--------------+------------+---------------
          True | Sonic the Hedgehog | Times Square | Saturday | 14:00:00.000000000 | Jeff Fowler | Ben Schwartz | 2021-02-02 | AMC Empire 25
    
  2. Show the current table, note the third line where the theater is now AMC Empire.

    SELECT * FROM movies.nowshowing;
    
     movie              | location     | run_day  | run_time           | director       | main_actor     | released   | theater
    --------------------+--------------+----------+--------------------+----------------+----------------+------------+--------------------
     Sonic the Hedgehog | Penn Station |   Sunday | 14:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 | AMC 34th Street 14
     Sonic the Hedgehog | Penn Station |   Sunday | 21:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 | AMC 34th Street 14
     Sonic the Hedgehog | Times Square | Saturday | 14:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 |         AMC Empire
     Sonic the Hedgehog | Times Square | Saturday | 21:00:00.000000000 |    Jeff Fowler |   Ben Schwartz | 2021-02-02 |      AMC Empire 25
          Invisible Man | Penn Station |   Sunday | 18:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 | AMC 34th Street 14
          Invisible Man | Penn Station |   Sunday | 22:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 | AMC 34th Street 14
          Invisible Man | Times Square |   Friday | 21:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 |      AMC Empire 25
          Invisible Man | Times Square | Saturday | 22:00:00.000000000 | Leigh Whannell | Elisabeth Moss | 2022-04-06 |      AMC Empire 25
    
    (8 rows)
    

Update a table using a conditional batch

Suppose you want to update the run time of a movie at a certain location. As the run time is part of the primary key, you cannot modify it. However, you can remove and re-insert the record.

  1. Run a batch job which removes and inserts a record:

    BEGIN BATCH
        DELETE FROM movies.nowshowing
        WHERE movie = 'Sonic the Hedgehog' AND location = 'Times Square'
          AND run_day = 'Saturday' AND run_time = '21:00:00'
        IF EXISTS
    
        INSERT INTO movies.nowshowing (movie, location, theater, run_day, run_time)
        VALUES ('Sonic the Hedgehog', 'Times Square', 'AMC Empire 25', 'Saturday', '23:00:00')
    APPLY BATCH;
    
  2. Show the current table

    SELECT * FROM movies.nowshowing;
    

Delete a partition using a conditional batch

The movie, “Invisible Man” is no longer being played so the theater wants to delete it. This involves creating a batch job which will:

  • Mark the batch as conditional to make it atomic

  • Delete the entire partition

  1. Run the following:

    BEGIN BATCH
        UPDATE movies.nowshowing SET released = NULL WHERE movie = 'Invisible Man' IF EXISTS
        DELETE FROM movies.nowshowing WHERE movie = 'Invisible Man'
    APPLY BATCH;
    

How is IF different from WHERE?

One may think that IF clause should be used in place of WHERE - and this is true to a large extent, both accept expressions and are applied to the searched row.

Unlike the WHERE clause, IF conditions never use a secondary index; as the rows are fetched before a condition is evaluated.

Keep in mind that the IF condition applies only to a fully qualified row, meaning you must specify the partition key and in many cases the clustering key as well. In the WHERE clause you would use DELETE or UPDATE or in SET. When using UPDATE and INSERT with WHERE you would also need the VALUES clause.

If your data selection fetches multiple rows, your IF condition cannot be ambiguous, meaning it can not evaluate to TRUE for one row and to FALSE for another. This includes statements which restrict only the partition key, and not the clustering key, or the partition key and multiple clustering keys (pk = ? and ck IN (?, ?, ?). In these instances, only the conditions on static cells are accepted.

Working with conditional statement result set

A conditional statement always returns a result set. The result set’s first column [applied] is special: it indicates whether the statement was applied or not. Following the [applied] column are the primary key columns and then the columns used in the conditional expression. The result set contains previous (old) values for these columns. If condition is IF EXISTS or IF NOT EXISTS all columns of the column family become part of the result set. If the statement inserts a new row so previous values did not exist, the result will contain NULLs.

A batch statement may contain multiple conditional statements. Each conditional statement of a batch yields a row of the result set, and these rows are returned in statement order. Non-conditional statements may be present in a conditional batch, but do not contribute to the result set. The set of columns of conditional batch result set is a set union of all columns used in conditional expressions of all conditional statements of the batch.

BEGIN BATCH
    UPDATE movies.nowshowing SET main_actor = 'Aldis Hodge' WHERE movie = 'Invisible Man' IF main_actor = 'Elisabeth Moss'
    UPDATE movies.nowshowing SET director = 'Mr Saw ' WHERE movie = 'Invisible Man' IF director = 'Leigh Whannell'
APPLY BATCH;

 [applied] | movie         | location | run_day | run_time | director       | main_actor
-----------+---------------+----------+---------+----------+----------------+----------------
      True | Invisible Man |     null |    null |     null | Leigh Whannell | Elisabeth Moss
      True | Invisible Man |     null |    null |     null | Leigh Whannell | Elisabeth Moss

Error handling

Error executing a conditional statement (LWT) does not necessarily mean it failed. In addition to standard causes for failure such as client-side timeouts, server overload, memory allocation error, Paxos has own scenarios leading to uncertainty:

  • An update started by one node is allowed to be overtaken and completed by another node.

  • The coordinator may fail or timeout after a write has succeeded at the majority of the participants and thus has de-facto committed.

To know for sure, a client must read the value back or retry the operation until it succeeds. Retrying should be done only if the failure is transient. It would be useless to retry in case of, e.g., a syntax error. Let’s consider some transient errors in more detail.

Error

Description

Unavailable exception

Indicates that the coordinator is unable to contact the number of replicas required by the statement consistency level. This can happen because one or more nodes are down. Alternatively, the ring simply may not have enough replicas to satisfy the keyspace replication factor. The coordinator performs availability checks independently for Paxos COMMIT and LEARN steps to satisfy SERIAL CONSISTENCY and CONSISTENCY settings respectively. Is a transient failure, unless the cluster is misconfigured. The step at which availability error had happened can be determined by the returned consistency level. If CL is SERIAL or LOCAL_SERIAL the failure happened before the statement could have any effect. Failures during LEARN, on the contrary, happen after the statement had already been committed by Paxos. CL for such failures would be ONE, QUORUM or similar.

Write timeout

A write timeout can happen at any step of Paxos. If it happens after the majority of the nodes has received the write, the write will be committed despite the failure.

Read timeout

Has the same meaning as Write timeout, but is returned for SELECTs. Internally, conditional updates may perform reads, but timeouts during these are still returned as write timeouts.

Limitations

The following limitations apply:

  • You cannot use conditional batches to modify multiple partitions

  • You cannot use LWT with tables which use counters

  • When using user-supplied timestamps, you must make sure that the timestamp is assigned by the transaction coordinator. If not, it will not be possible to guarantee consistency.

  • It is not recommended to use conditional (LWT) and non-conditional statements with the same data set as it is not possible to ensure that conditional statements are consistent in this case. In short, all LWT data sets should not use write operations that are not LWT in structure.

Other limitations are more minor:

  • While a non-LWT batch can be UNLOGGED, a conditional batch cannot;

  • IF conditions must be a perfect conjunct (… AND … AND …);

  • Unlike Cassandra, Scylla doesn’t have LWT support in Thrift protocol and doesn’t plan to add it;

  • Conditional batches are always logged in system.paxos table, so UNLOGGED keyword is silently ignored for them.

Additional Information