VoltDB
6.6.8
Novermber 22, 2017
This document provides information about known issues and limitations to the current release of VoltDB. If you encounter any problems not listed below, please be sure to report them to [email protected]. Thank you.
The process for upgrading from a previous version of VoltDB is as follows:
Place the database in admin mode (using voltadmin pause).
Perform a manual snapshot of the database (using voltadmin save --blocking).
Shutdown the database (using voltadmin shutdown).
Upgrade the VoltDB software.
Initialize a new database root directory (using the voltdb init --force action).
Start the database in admin mode (using the voltdb start --pause action).
Restore the snapshot created in Step #2 (using voltadmin restore).
Return the database to normal operations (using voltadmin resume).
For customers upgrading from version 5.9 or later, it is possible to minimize the downtime required for the upgrade by performing a "hot" upgrade across clusters using database replication (DR). See the section on upgrading across clusters in the VoltDB Administrator's Guide for more information.
For customers upgrading from V5.x or earlier releases of VoltDB, please see the V5.0 Upgrade Notes.
For customers upgrading from V4.x or earlier releases of VoltDB, please see the V4.0 Upgrade Notes.
Users of previous versions of VoltDB should take note of the following changes that might impact their existing applications.
1. Release V6.6.8 (Novermber 22, 2017) | |
1.1. | Recent improvements |
The following limitations in previous versions have been resolved:
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2. Release V6.6.7 (June 23, 2017) | |
2.1. | Recent improvements |
The following limitations in previous versions have been resolved:
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3. Release V6.6.6 (February 21, 2017) | |
3.1. | Recent improvements |
The following limitations in previous versions have been resolved:
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4. Release V6.6.5 (February 3, 2017) | |
4.1. | Recent improvements |
The following limitation in previous versions have been resolved:
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5. Release V6.6.4 (December 30, 2016) | |
5.1. | Recent improvements |
The following limitations in previous versions have been resolved:
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6. Release V6.6.3 (November 28, 2016) | |
6.1. | Recent improvements |
The following limitations in previous versions have been resolved:
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7. Release V6.6.2 (November 21, 2016) | |
7.1. | NoSuchElementException when running XDCR |
There was a race condition in earlier releases where cross data center replication (XDCR) could be terminated, reporting the error "NoSuchElementException". The clusters remained active but no further replication occurred until DR was reset and restarted. This issue has been resolved. | |
8. Release V6.6.1 (November 17, 2016) | |
There were two issues, specific to V6.6, that are resolved in this release. | |
8.1. | Slow DR performance and out-of-memory issues |
Database replication (DR) supports different topologies on the two clusters. To achieve this, if single-partitioned procedures attempt to update records including different partition column values, the consumer cluster may have to redirect the write operations, essentially turning the single-partition procedure into a multi-partition transaction. This is most notable for actions such as batch inserts using utilities such as csvloader. However, for V6.6, this operation was not optimized to remain single-partitioned if the clusters had the same topology. As a consequence, when using DR with many multi-partition transactions or large single-partition transactions involving multiple partition column values, performance suffered and the cluster could ultimately crash with an out of memory error. This problem is resolved in 6.6.1 and later releases. | |
8.2. | Multi-partition deadlock on node failure |
In certain rare cases, a node failure in a K-safe V6.6 cluster could result in the database hanging reporting a multi-partition deadlock. This issue is specific to V6.6. and is resolved in all later versions. | |
8.3. | Additional improvements |
In addition to the preceding V6.6-specific fixes, the following limitation has been resolved:
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9. Release V6.6 (September 8, 2016) | |
9.1. | New VoltDB command line |
Beta testing of the new command line is complete. The new, improved commands init and start are ready for production use and are the recommended method for running VoltDB, replacing the legacy commands create, recover, rejoin, and add. The new commands are described in the reference page for the voltdb command. The example applications that come with the VoltDB software use the new commands. The remainder of the documentation will be updated to reflect the new commands over the next few releases. | |
9.2. | Separate resource paths per server using new command line |
When initializing the database root directories for a cluster with the voltdb init command, each server can specify separate paths for its resources. For example, the database root itself can be different. Also explicit paths in the deployment file, such as the paths for command logs, export overflow, snapshots, etc can be unique per server if you wish. These path attributes are not checked when comparing the deployment files between servers on cluster startup. | |
9.3. | Support for running different versions of VoltDB on XDCR clusters |
It is now possible to use different versions of VoltDB on the two clusters used for cross data center replication (XDCR). The main use of this capability is to allow "live" software upgrades of VoltDB by upgrading each cluster in sequence. See the section on "Upgrading VoltDB Software" in the VoltDB Administrator's Guide for more information. (Note that running different versions for an extended period is not recommended, due to incompatibilities resulting from new SQL syntax introduced by later versions of the software.) | |
9.4. | Joins in views |
VoltDB now supports joining multiple tables in a view using inner joins. For best performance, having an index on the joining column(s) is strongly recommended. See the description of the CREATE VIEW statement in the Using VoltDB manual for details. | |
9.5. | RANK() window function in the selection list |
VoltDB also now supports use of the RANK() window function in the selection list of a SELECT statement. For example: SELECT city, population, RANK() OVER (ORDER BY population) FROM cities... See the description of the SELECT statement in the Using VoltDB manual for details. | |
9.6. | Improvements to snapshots |
The following improvements have been made to saving and restoring snapshots:
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9.7. | New trigonometric functions |
New SQL functions for sine, cosine, tangent, secant, cosecant, and cotangent are available. The functions are SIN(), COS(), TAN(), SEC(), CSC(), and COT(), and take one numeric argument representing an angle measured in radians. See the appendix of SQL functions in the Using VoltDB manual for details. | |
9.8. | More flexibility for SQL functions without input arguments |
SQL functions that do not require any input arguments, such as NOW() and PI(), can now be specified either with or without the parentheses. Previously, some functions required the parentheses and some did not accept them. Both forms are now allowed. For example, the current timestamp value can be specified as either CURRENT_TIMESTAMP() or CURRENT_TIMESTAMP. | |
9.9. | New directives in sqlcmd to echo text to the output |
Two new directives, ECHO and ECHOERROR, let you write comments into the output of the sqlcmd utility. Each directive writes any following text on the line, as is, to standard output or standard error, respectively. See the sqlcmd command in the Using VoltDB manual for details. | |
9.10. | Heap size recommendations in VoltDB Management Center |
The web-based VoltDB Management Center now includes recommended settings for the Java heap in the sizing worksheet. The recommendations are based on the current database schema, plus the desired cluster configuration and estimated data volume. After starting the database, go to the Management Center (http://{server-address}:8080), click on the Schema tab and then Size Worksheet to use the worksheet. The Management Center also includes the current and recommended heap settings for the current configuration in the Overview section of the Schema tab. | |
9.11. | Support for Ubuntu 16.04 |
VoltDB now supports Ubuntu 16.04 as a base platform for production usage. | |
9.12. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
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10. Release V6.5 (July 28, 2016) | |
10.1. | Simplified VoltDB command line (BETA) |
This release introduces new, improved commands for starting VoltDB database servers. The new command line will ultimately replace the create, recover, rejoin, and add commands with just two commands: init and start. The new commands are available for beta testing and are described in a separate beta release letter. Both new and old commands will be supported for the remaining 6.x releases. However, the old commands will be deprecated in the future so we encourage all interested customers to try the new commands and provide feedback to ensure they meet your needs. Thank you. | |
10.2. | Improved performance of large schema updates |
Changes have been made to how VoltDB distributes schema updates (including adding and removing stored procedures) to cluster nodes. These changes can significantly reduce the time required for the schema update to complete on clusters with a large number of sites per host. | |
10.3. | New, improved VoltDB clients for ODBC and Go |
Improved clients for ODBC and the Go programming language are being released simultaneously with this release of VoltDB. The Go client now supports client affinity, standard Go syntax for connecting to a database, as well as automatically reconnecting to broken connections. Both clients will be available from the VoltDB web site client download page. | |
10.4. | Support for FULL OUTER JOIN |
The VoltDB SELECT statement now supports full outer joins. | |
10.5. | New SQL functions to validate TIMESTAMP values |
TIMESTAMP values are stored as eight-byte integers. It is possible to enter an eight-byte numeric value that is not actually a valid timestamp. The new functions MIN_VALID_TIMESTAMP() and MAX_VALID_TIMESTAMP() give you access to the valid minimum and maximum values. The function IS_VALID_TIMESTAMP() compares a TIMESTAMP value and returns true or false depending on whether the value falls within the valid range or not. See the appendix of SQL functions in the Using VoltDB manual for details. | |
10.6. | Ability to use boolean literals in SQL conditional expressions |
It is now possible to use boolean literals — such as TRUE and FALSE or 1=1 and 1=0 — when evaluating conditional expressions in SQL statements. For example: SELECT Silos FROM Barns WHERE TRUE; SELECT Rooms FROM Houses WHERE 1=0; | |
10.7. | The csvloader utility can now interpret header rows |
The csvloader utility has a new argument, --header, which indicates that the first row of data is a header row containing the names of the columns. These column names must match names of columns in the database table. By using --header, the columns in the CSV file can be in a different order than the table columns. Also, the CSV file can have a subset of columns, as long as the missing columns are declared with a default value or not explicitly NOT NULL in the database schema. See the description of the csvloader utility in the Using VoltDB manual for details. | |
10.8. | Improved handling of missing servers in sqlcmd --servers list |
The sqlcmd utility lets you specify multiple servers to connect to using the --servers argument. However, previously if any of the listed servers were unavailable, sqlcmd would not start. Now, sqlcmd ignores unavailable servers and will continue as long as at least one of the listed servers is accessible. | |
10.9. | When restoring data, constraint violations no longer stop the database. |
Previously, any constraint violation during a restore operation, was interpreted as a fatal error and stopped the database. This behavior has changed. Constraint violations during restore are now reported as warnings and the data records logged to a CSV file. This allows you to restore as much data as possible and resolve the constraint violations manually once the restore operation completes. | |
10.10. | Automatic reconnection added to JDBC driver |
The VoltDB JDBC driver can now automatically reconnect to lost connections. To enable this feature, you add an argument to the connection string, like so: Connection c = DriverManager.getConnection( "jdbc:voltdb://svr1:21212,svr2:21212?autoreconnect=true"); See the section on the JDBC interface in the Using VoltDB manual for details. | |
10.11. | New option to control whether the JDBC export connector creates tables in the target database |
There is a new parameter for the JDBC export connector that lets you specify whether the
connector should automatically create tables matching the export streams in the target database. The new parameter
is | |
10.12. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
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11. Release V6.4 (June 24, 2016) | |
11.1. | Heterogeneous XDCR clusters |
It is now possible to use Cross Datacenter Replication (XDCR) to perform active replication between clusters of different sizes. That is, clusters with a different number of nodes, K-safety, or sites per host. | |
11.2. | Additional information in the XDCR conflict logs |
The conflict logs for Cross Datacenter Replication (XDCR) contain additional information. Two new columns were added to record the timestamp when the conflict occurred and the ID of the cluster reporting the conflict. These are in addition to the existing columns recording the timestamp and cluster ID of the transaction that generates the conflict. Also an extra row marked as DEL is added when the conflict is the result of a DELETE operation. See the chapter on Database Replication in the Using VoltDB manual for more information. | |
11.3. | Ability to use SSL for VoltDB web interface |
You can now enable encryption for the VoltDB httpd port, which is used for the JSON interface and access to the VoltDB Management Center. This means all access to these features will use the HTTPS protocol rather than the unencrypted HTTP. You enable HTTPS in the deployment file. See the appendix on Server Configuation Options in the VoltDB Administrator's Guide for more information. | |
11.4. | Ability to turn on admin mode from the command line when starting VoltDB |
Previously, admin mode could be enabled when starting the cluster only by modifying the deployment file before starting. This is not an ideal approach for a setting that can be changed at runtime. So starting with 6.4 turning on admin mode on start is done through a new command line flag, --pause. By adding --pause to the voltdb create or voltdb recover command, you can start the cluster in admin mode, which is handy when wanting to perform administrative tasks, such as modifying the schema or restoring a snapshot, before allowing clients full read/write access. (Use of the deployment file to enable admin mode is still supported, but deprecated in favor of the new command line flag.) | |
11.5. | New and enhanced SQL functions |
Three new SQL functions have been added:
In addition, the MOD() function has been enhanced to operate on either DECIMAL or INTEGER values. ee the appendix on SQL Functions in the Using VoltDB for more information. | |
11.6. | Kinesis import and export and new import properties |
A new source for the VoltDB importer, Amazon Kinesis, is now available. Kinesis joins Kafka as the supported sources for import. There is also an export connector for Amazon Kinesis available from the VoltDB public Github repository (https://github.com/VoltDB/export-kinesis). In addition, new properties have been added to control the operation of the import CSV and TSV formatters. See the chapter on Importing and Exporting Live Data in the Using VoltDB for more information. | |
11.7. | Improved read level consistency during network partitions |
A potential read consistency issue was identified and resolved. Read transactions can access data modified by write transactions on the local server, before all nodes confirm those write transactions. During a node failure or network partition, it is possible that the locally completed writes could be rolled back as part of the network partition resolution. This could only happen in the off chance that the read transaction accesses data modified by an immediately preceding write that has not been committed on all copies of the partition prior to a network partition. But to ensure this cannot happen, reads now run on all copies of the partition, guaranteeing consensus among the servers and complete read consistency. However, it also incrementally increases the time required to complete a read-only transaction in a K-safe cluster. If you do not need complete read consistency, you can optionally set the cluster to produce faster read transactions using the old behavior, by setting the read level consistency to "fast" in the deployment file. See the appendix on Server Configuration Options in the VoltDB Administrator's Guide for more information. | |
11.8. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
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12. Release V6.3 (May 17, 2016) | |
12.1. | Changing schema during Database Replication (DR) |
It is now possible to modify DR tables. In passive replication, changing the schema of DR tables on the master database automatically pauses DR on the replica until you make matching schema changes there. In cross data center replication (XDCR), you should pause both clusters and ensure all binary logs have been processed before making the schema changes and resume on both databases. See the chapter on Database Replication in the Using VoltDB manual for more information. | |
12.2. | More examples, better notes |
The examples in the VoltDB kit have been reorganized and significantly expanded. Some of the new examples demonstrate call center tracking, mobile ads, and managing time windows for selectively deleting old data. See the README.md file in the /examples folder for more information and a complete list of examples. | |
12.3. | Support for geospatial data in export and the JDBC interface |
VoltDB now supports exporting geospatial columns through the export connectors, where the data is converted to well-known text (WKT) strings. This release also adds support for the JDBC setObject and getObject methods for converting geospatial data natively to and from the VoltDB GeographyValue and GeographyPoinValue types in Java to the database GEOGRAPHY and GEOGRAPHY_POINT datatypes. | |
12.4. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
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13. Release V6.2.1 (April 29, 2016) | |
13.1. | Recent improvement |
The following limitation has been resolved:
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14. Release V6.2 (April 12, 2016) | |
14.1. | Support for different cluster sizes in passive Database Replication (DR) |
Previously, passive Database Replication (DR) required both the master and replica clusters to have the same configuration; that is, the same number of nodes, sites per host, K factor, and so on. You can now use different size clusters for passive DR. You can even use different values for partition row limits on DR tables. However, be aware that using a smaller replica cluster could potentially lead to memory limitation issues. Be sure to configure both clusters with sufficient capacity for the expected volume of data. | |
14.2. | VoltDB avoids overwriting existing database files in the voltdbroot directory |
The behavior of the voltdb create command has changed. If you attempt to create a new database in a voltdbroot directory that contains command logs, snapshots, or other artifacts of a previous session, the voltdb create command issues an error. This behavior is to avoid you accidentally deleting data when you should be using the voltdb recover command. You can override this default behavior by adding the --force argument to the voltdb create command to explicitly overwrite files from the previous database session. | |
14.3. | New function creates and validates GEOGRAPHY data in single step |
The POLYGONFROMTEXT() converts well-known text (WKT) representations of polygons to the GEOGRAPHY datatype and the ISVALID() function verifies that the resulting polygon meets the requirements for VoltDB. The new function, VALIDPOLYGONFROMTEXT() performs both steps in a single function, returning an error if the resulting polygon is not valid. | |
14.4. | Support for geospatial datatypes in C++ client API |
The VoltDB C++ client API now supports use of the geospatial datatypes GEOGRAPHY and GEOGRAPHY_POINT. | |
14.5. | VoltDB command line utilities now prompt for the password |
If you specify a username on the command line but not a password, the VoltDB command lines utilities such as sqlcmd and csvloader will prompt you for the password. This feature is useful if you are scripting commands for a VoltDB database with security enabled. You no longer need to hardcode passwords into the script. | |
14.6. | Availability of the VoltDB Deployment Manager |
The VoltDB Deployment Manager is now available for general use. The Deployment Manager lets you configure and start VoltDB clusters using either a web-based interface or a programmable REST API. See the chapter on "Deploying Clusters Using the VoltDB Deployment Manager" in the VoltDB Administrator's Guide for details. | |
14.7. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
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15. Release V6.1 (March 4, 2016) | |
15.1. | New streaming data capabilities |
This release introduces a new concept in VoltDB: streams. Streams act like virtual tables. You declare them like tables using the CREATE STREAM statement and you insert data into the stream using the INSERT statement. However, data inserted into a stream is not actually stored in the database. Data inserted into a stream can be analyzed (using views) and streamed directly to other business systems (using export). To analyze streaming data, you define a stream using the CREATE STREAM statement, then define a view on that stream using the CREATE VIEW statement. This view allows you to perform summary analysis on the data as it passes through the database without paying the penalty of actually storing the data, all in a transactionally consistent way. Although you cannot modify the underlying data of such views — because the stream is transient — views on streams are unique in that you can update the view itself if needed. For example, you can create a daily summary of a stream by resetting the view's values to zero at midnight using a DELETE FROM {view-name} or UPDATE {view-name} statement. You can also export data from streams to external systems using VoltDB's existing export infrastructure. In fact, streams replace the old EXPORT TABLE concept. Instead of defining a table then declaring it as an export table, you now define a stream and assign it to an export target all in one statement. For example: CREATE STREAM visits EXPORT TO TARGET archive ( user_id BIGINT NOT NULL, login TIMESTAMP ); In the export deployment configuration, the old stream attribute is now replaced by target, to make the terminology consistent. Note that, although the EXPORT TABLE DDL statement and the deployment stream attribute are now deprecated, they will still be supported for backwards compatibility until some future major release. See the description of the CREATE STREAM statement in the Using VoltDB manual for more information. | |
15.2. | Support for indexes on geospatial GEOGRAPHY columns |
VoltDB now supports GEOGRAPHY columns in indexes. The index can be applied to instances of the CONTAINS() function where the indexed column is the first argument. For example, an index including the GEOGRAPHY column border could optimize the following query: SELECT assets.id, counties.county, counties.state FROM counties, assets WHERE CONTAINS(counties.border, assets.loc); | |
15.3. | New boolean function for measuring geospatial distances |
The new geospatial function DWITHIN() determines if two geospatial values (two points or a point and a geographical region) are within a specified distance of each other. For example, the following query returns all the restaurants within 5,000 meter of a tourist: SELECT r.name, r.address, DISTANCE(r.loc,t.loc) FROM restaurants AS r, tourists AS t WHERE DWITHIN(r.loc, t.loc,5000) AND t.id = ? ORDER BY DISTANCE(r.loc,t.loc) ASC; | |
15.4. | Ability to load geospatial values with the csvloader |
The csvloader now supports the ability to load values into geospatial columns (GEOGRAPHY or GEOGRAPHY_POINT) by including the values as well-known text (WKT) in the CSV input. See the chapter on "Creating Geospatial Applications" in the VoltDB Guide to Performance and Customization for information on creating WKT compatible with the grospatial datatypes. | |
15.5. | Beta release of VoltDB Deployment Manager |
We are working on a new deployment process for configuring and starting VoltDB clusters. The VoltDB Deployment Manager is a daemon process that supports both a RESTful API for scripting and an fully interactive web interface. Although not ready for production use, a beta version is included in the current software kits. Customers interested in trying out the new Deployment Manager and providing feedback should contact VoltDB support for more information. | |
15.6. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
| |
16. Release V6.0.1 (February 24, 2016) | |
16.1. | Performance tuning for cross datacenter replication (XDCR) |
When running in virtualized environments, it is possible for the thread that creates binary logs for database replication (DR) to compete with transactions on the local cluster, causing occasional increased latency. To mitigate this situation, the initial size of the buffer for binary logs has been changed to 512KB, which is optimized for most workloads. However, If your workload is observing long latencies when running cross datacenter replication (XDCR), you may need to adjust the size of the buffer. To change the default buffer size, set the VoltDB variable DDR_DEFAULT_BUFFER_SIZE before starting the database process, specifying the size in bytes: export VOLTDB_OPTS="-DDR_DEFAULT_BUFFER_SIZE=nnnn" | |
16.2. | Recent improvements |
The following limitations in previous versions have been resolved:
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17. Release V6.0 (January 26, 2016) | |
17.1. | Updated operating system and software requirements |
The operating system and software requirements for VoltDB have been updated based on changes to the supported versions of the underlying technologies. Specifically:
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17.2. | Memory resource monitoring is on by default |
Resource monitoring is enabled by default with a memory limit of 80%. If memory usage exceeds this limit, the database is placed in read-only mode until usage drops below the limit. You can alter the resource limits in the deployment file. See the section on resource monitoring in the VoltDB Administrator's Guide for details. | |
17.3. | New geospatial datatypes and functions |
VoltDB now supports two new datatypes, GEOGRAPHY and GEOGRAPHY_POINT, and several new functions optimized for geospatial data. These datatypes are fully integrated in the VoltDB durability features such as snapshots and command logging. However, tables containing geospatial columns are not currently supported for export or database replication (DR). Integration of these capabilities will be added in a future release. | |
17.4. | Kerberos support for VoltDB Management Center and JSON interface |
VoltDB now supports Kerberos security for the VoltDB Management Center (VMC) and the JSON interface. To allow access from VMC and JSON, the server JAAS login configuration must include two additional entries for the Java Generic Security Service (JGSS): one for the VoltDB service principle and one for the server's HTTP service principle. | |
17.5. | JMX support deprecated |
The VoltDB Enterprise Manager, which was deprecated in V5.0, has been removed from the kit. JMX support, which was added for the Enterprise Manager, is now deprecated. See the chapter on database monitoring in the VoltDB Administrator's Guide for alternative ways to monitor your database. | |
17.6. | Additional improvements |
In addition to the new features and capabilities described above, the following limitations in previous versions have been resolved:
|
The following are known limitations to the current release of VoltDB. Workarounds are suggested where applicable. However, it is important to note that these limitations are considered temporary and are likely to be corrected in future releases of the product.
1. Command Logging | |
1.1. | Changing the deployment configuration when recovering command logs, can result in unexpected settings. |
There is an issue where, if the command log contains schema changes (performed through interactive DDL statements, voltadmin update, or @UpdateApplicationCatalog), when the command logs are recovered, the previous deployment file settings are used, even if an alternate deployment file is specified on the voltdb recover command line. Then, after recovering the database, a new schema update can result in the deployment settings specified on the command line taking affect. Until this issue is resolved, the safest workaround to ensure the desired configuration is achieved is to perform the voltdb recover operation without modifying the current deployment file, then make deployment changes with the voltadmin update command after the database has started. | |
1.2. | Command logs can only be recovered to a cluster of the same size. |
To ensure complete and accurate restoration of a database, recovery using command logs can only be performed to a cluster with the same number of unique partitions as the cluster that created the logs. If you restart and recover to the same cluster with the same deployment options, there is no problem. But if you change the deployment options for number of nodes, sites per host, or K-safety, recovery may not be possible. For example, if a four node cluster is running with four sites per host and a K-safety value of one, the cluster has two copies of eight unique partitions (4 X 4 / 2). If one server fails, you cannot recover the command logs from the original cluster to a new cluster made up of the remaining three nodes, because the new cluster only has six unique partitions (3 X 4 / 2). You must either replace the failed server to reinstate the original hardware configuration or otherwise change the deployment options to match the number of unique partitions. (For example, increasing the site per host to eight and K-safety to two.) | |
1.3. | Do not use the subfolder name "segments" for the command log snapshot directory. |
VoltDB reserves the subfolder "segments" under the command log directory for storing the actual command log files. Do not add, remove, or modify any files in this directory. In particular, do not set the command log snapshot directory to a subfolder "segments" of the command log directory, or else the server will hang on startup. | |
2. Database Replication | |
2.1. | Some DR data may not be delivered if master database nodes fail and rejoin in rapid succession. |
Because DR data is buffered on the master database and then delivered asynchronously to the replica, there is always the danger that data does not reach the replica if a master node stops. This situation is mitigated in a K-safe environment by all copies of a partition buffering on the master cluster. Then if a sending node goes down, another node on the master database can take over sending logs to the replica. However, if multiple nodes go down and rejoin in rapid succession, it is possible that some buffered DR data — from transactions when one or more nodes were down — could be lost when another node with the last copy of that buffer also goes down. If this occurs and the replica recognizes that some binary logs are missing, DR stops and must be restarted. To avoid this situation, especially when cycling through nodes for maintenance purposes, the key is to ensure that all buffered DR data is transmitted before stopping the next node in the cycle. You can do this using the @Statistics system procedure to make sure the last ACKed timestamp (using @Statistitcs DR on the master cluster) is later than the timestamp when the previous node completed its rejoin operation. | |
2.2. | Avoid bulk data operations within a single transaction when using database replication |
Bulk operations, such as large deletes, inserts, or updates are possible within a single stored procedure. However, if the binary logs generated for DR are larger than 45MB, the operation will fail. To avoid this situation, it is best to break up large bulk operations into multiple, smaller transactions. A general rule of thumb is to multiply the size of the table schema by the number of affected rows. For deletes and inserts, this value should be under 45MB to avoid exceeding the DR binary log size limit. For updates, this number should be under 22.5MB (because the binary log contains both the starting and ending row values for updates). | |
2.3. | Database replication ignores resource limits |
There are a number of VoltDB features that help manage the database by constraining memory size and resource utilization. These features are extremely useful in avoiding crashes as a result of unexpected or unconstrained growth. However, these features could interfere with the normal operation of DR when passing data from one cluster to another, especially if the two clusters are different sizes. Therefore, as a general rule of thumb, DR overrides these features in favor of maintaining synchronization between the two clusters. Specifically, DR ignores any resource monitor limits defined in the deployment file when applying binary logs on the consumer cluster. DR also ignores any partition row limits defined in the database schema when applying binary logs. This means, for example, if the replica database in passive DR has less memory or fewer unique partitions than the master, it is possible that applying binary logs of transactions that succeeded on the master could cause the replica to run out of memory. Note that these resource monitor and tables row limits are applied on any original transactions local to the cluster (for example, transactions on the master database in passive DR). | |
2.4. | Different cluster sizes can require additional Java heap |
Database Replication (DR) now supports replication across clusters of different sizes. However, if the replica cluster is smaller than the master cluster, it may require a significantly larger Java heap setting. Specifically, if the replica has fewer unique partitions than the master, each partition on the replica must manage the incoming binary logs from more partitions on the master, which places additional pressure on the Java heap. A simple rule of thumb is that the worst case scenario could require an additional P * R * 20MB space in the Java heap , where P is the number of sites per host on the replica server and R is the ratio of unique partitions on the master to partitions on the replica. For example, if the master cluster is 5 nodes with 10 sites per host and a K factor of 1 (i.e. 25 unique partitions) and the replica cluster is 3 nodes with 8 sites per host and a K factor of 1 (12 unique partitions), the Java heap on the replica cluster may require approximately 320MB of additional space in the heap: Sites-per-host * master/replace ratio * 20MB An alternative is to reduce the size of the DR buffers on the master cluster by setting the DR_MEM_LIMIT Java property. For example, you can reduce the DR buffer size from the default 10MB to 5MB using the VOLTDB_OPTS environment variable before starting the master cluster. $ export VOLTDB_OPTS="-DDR_MEM_LIMIT=5" $ voltdb create Changing the DR buffer limit on the master from 10MB to 5MB proportionally reduces the additional heap size needed. So in the previous example, the additional heap on the replica is reduced from 320MB to 160MB. | |
3. Cross Datacenter Replication (XDCR) | |
3.1. | Avoid replicating tables without a unique index. |
Part of the replication process for XDCR is to verify that the record's starting and ending states match on both clusters, otherwise known as conflict resolution. To do that, XDCR must find the record first. Finding uniquely indexed records is efficient; finding non-unique records is not and can impact overall database performance. To make you aware of possible performance impact, VoltDB issues a warning if you declare a table as a DR table and it does not have a unique index. | |
3.2. | When starting XDCR for the first time, only one database can contain data. |
You cannot start XDCR if both databases already have data in the DR tables. Only one of the two participating databases can have preexisting data when DR starts for the first time. | |
3.3. | During the initial synchronization of existing data, the receiving database is paused. |
When starting XDCR for the first time, where one database already contains data, a snapshot of that data is sent to the other database. While receiving and processing that snapshot, the receiving database is paused. That is, it is in read-only mode. Once the snapshot is completed and the two database are synchronized, the receiving database is automatically unpaused, resuming normal read/write operations. | |
3.4. | A large number of multi-partition write transactions may interfere with the ability to restart XDCR after a cluster stops and recovers. |
Normally, XDCR will automatically restart where it left off after one of the clusters stops and recovers from its command logs (using the voltdb recover command). However, if the workload is predominantly multi-partition write transactions, a failed cluster may not be able to restart XDCR after it recovers. In this case, XDCR must be restarted from scratch, using the content from one of the clusters as the source for synchronizing and recreating the other cluster (using the voltdb create --force command) without any content in the DR tables. | |
3.5. | A TRUNCATE TABLE transaction will be reported as a conflict with any other write operation to the same table. |
When using XDCR, if the binary log from one cluster includes a TRUNCATE TABLE statement and the other cluster performs any write operation to the same table before the binary log is processed, the TRUNCATE TABLE operation will be reported as a conflict. Note that currently DELETE operations always supercede other actions, so the TRUNCATE TABLE will be executed on both clusters. | |
3.6. | Exceeding a LIMIT PARTITION ROWS constraint can generate multiple conflicts |
It is possible to place a limit on the number of rows that any partition can hold for a specific table using the LIMIT PARTITION ROWS clause of the CREATE TABLE statement. When close to the limit, transactions on either or both clusters can exceed the limit simultaneously, resulting in a potentially large number of delete operations that then generate conflicts when the the associated binary log reaches the other cluster. | |
3.7. | Use of the VoltProcedure.getUniqueId method is unique to a cluster, not across clusters. |
VoltDB provides a way to generate a deterministically unique ID within a stored procedure using the getUniqueId method. This method guarantees uniqueness within the current cluster. However, the method could generate the same ID on two distinct database clusters. Consequently, when using XDCR, you should combine the return values of VoltProcedure.getUniqueId with VoltProcedure.getClusterId, which returns the current cluster's unique DR ID, to generate IDs that are unique across all clusters in your environment. | |
4. Export | |
4.1. | Synchronous export in Kafka can use up all available file descriptors and crash the database. |
A bug in the Apache Kafka client can result in file descriptors being allocated but not released if the producer.type attribute is set to "sync" (which is the default). The consequence is that the system eventually runs out of file descriptors and the VoltDB server process will crash. Until this bug is fixed, use of synchronous Kafka export is not recommended. The workaround is to set the Kafka producer.type attribute to "async" using the VoltDB export properties. | |
5. Import | |
5.1. | Data may be lost if a Kafka broker stops during import. |
If, while Kafka import is enabled, the Kafka broker that VoltDB is connected to stops (for example, if the server crashes or is taken down for maintenance), some messages may be lost between Kafka and VoltDB. To ensure no data is lost, we recommend you disable VoltDB import before taking down the associated Kafka broker. You can then re-enable import after the Kafka broker comes back online. | |
5.2. | Kafka import may be reset, resulting in duplicate entries. |
There is an issue with Kafka and the VoltDB Kafka importer where the current pointer in the Kafka queue gets reset to zero. The consequence of this event is that items in the queue get imported a second time resulting in duplicate entries. This issue will be addressed in an upcoming release. In the meantime, if you are using the Kafka importer, contact [email protected] for details. | |
6. SQL and Stored Procedures | |
6.1. | Comments containing unmatched single quotes in multi-line statements can produce unexpected results. |
When entering a multi-line statement at the sqlcmd prompt, if a line ends in a comment (indicated by two hyphens) and the comment contains an unmatched single quote character, the following lines of input are not interpreted correctly. Specifically, the comment is incorrectly interpreted as continuing until the next single quote character or a closing semi-colon is read. This is most likely to happen when reading in a schema file containing comments. This issue is specific to the sqlcmd utility. A fix for this condition is planned for an upcoming point release | |
6.2. | Do not use assertions in VoltDB stored procedures. |
VoltDB currently intercepts assertions as part of its handling of stored procedures. Attempts to use assertions in stored procedures for debugging or to find programmatic errors will not work as expected. | |
6.3. | The UPPER() and LOWER() functions currently convert ASCII characters only. |
The UPPER() and LOWER() functions return a string converted to all uppercase or all lowercase letters, respectively. However, for the initial release, these functions only operate on characters in the ASCII character set. Other case-sensitive UTF-8 characters in the string are returned unchanged. Support for all case-sensitive UTF-8 characters will be included in a future release. | |
7. Client Interfaces | |
7.1. | Avoid using decimal datatypes with the C++ client interface on 32-bit platforms. |
There is a problem with how the math library used to build the C++ client library handles large decimal values on 32-bit operating systems. As a result, the C++ library cannot serialize and pass Decimal datatypes reliably on these systems. Note that the C++ client interface can send and receive Decimal values properly on 64-bit platforms. |
The following notes provide details concerning how certain VoltDB features operate. The behavior is not considered incorrect. However, this information can be important when using specific components of the VoltDB product.