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database manualOutdated translations are marked like this.From the maintenance directory run:Alternatively you can provide a filename, and MediaWiki will execute it, substituting any MW special variables as appropriate. For more information, see Manual:Sql.php.However, the prompt is not as full features as the command line clients that come with your database.An instance of this class can be acquired by calling getConnectionRef() (preferred) or getConnection() on an injected ILoadBalancer. The function wfGetDB() is being phased out and should not be used in new code.Or to be precise, a subsequent write query which succeeded on the master may fail when replicated to the replica due to a unique key collision. Replication on the replica will stop and it may take hours to repair the database and get it back online.They can take care of things like table prefixes and escaping for you under some circumstances. If you really need to make your own SQL, please read the documentation for tableName() and addQuotes(). You will need both of them. Please keep in mind that failing to use addQuotes() properly can introduce severe security holes into your wiki.There is also good support for SQlite, however it is much slower than MySQL or MariaDB. There is support for PostgreSQL, but it is not as stable as MySQL. MediaWiki has experimental support for Oracle and MSSQL.For a detailed description of the parameters of the wrapper functions, please refer to class Database 's docs.The components of the SELECT statement are coded as parameters of the select() function. An example isIf you pass in strings to the third or fifth argument, you must manually use Database::addQuotes() on your values as you construct the string, as the wrapper will not do this for you. The values for table names (1st argument) or field names (2nd argument) must not be user controlled.A full example might be:For example:Patches containing unacceptably slow features will not be accepted.http://www.clsc.pl/files/exmark-lz27kc604-parts-manual.xml
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Unindexed queries are generally not welcome in MediaWiki, except in special pages derived from QueryPage. It's a common pitfall for new developers to submit code containing SQL queries which examine huge numbers of rows.Writes on the master are executed in parallel, but they are executed in serial when they are replicated to the replicas. The master writes the query to the binlog when the transaction is committed. The replicas poll the binlog and start executing the query as soon as it appears. They can service reads while they are performing a write query, but will not read anything more from the binlog and thus will perform no more writes. This means that if the write query runs for a long time, the replicas will lag behind the master for the time it takes for the write query to complete.MediaWiki's load balancer will stop sending reads to a replica when it is lagged by more than 30 seconds. If the load ratios are set incorrectly, or if there is too much load generally, this may lead to a replica permanently hovering around 30 seconds lag. All edits and other write operations will be refused, with an error returned to the user. This gives the replicas a chance to catch up. Before we had this mechanism, the replicas would regularly lag by several minutes, making review of recent edits difficult.A few seconds of lag can be tolerated, as long as the user sees a consistent picture from subsequent requests. This is done by saving the master binlog position in the session, and then at the start of each request, waiting for the replica to catch up to that position before doing any reads from it. The only practical consequence at present is a warning displayed in the page footer.Multi-row INSERT. SELECT queries are the worst offenders and should be avoided altogether. Instead do the select first and then the insert.Replication lag will usually be less than one second, but may occasionally be up to 30 seconds.http://metabolit.ru/files/file/exmark-lz25kc604-manual.xml For scalability, it's very important to keep load on the master low, so simply sending all your queries to the master is not the answer. So when you have a genuine need for up-to-date data, the following approach is advised:In most cases you should just read from the replica and let the user deal with the delay.By default, MediaWiki opens a transaction at the first query, and commits it before the output is sent. Locks will be held from the time when the query is done until the commit. So you can reduce lock time by doing as much processing as possible before you do your write queries.Use the following syntax:They are poorly implemented in InnoDB and will cause regular deadlock errors. It's also surprisingly easy to cripple the wiki with lock contention.Then use the affected row count to see if the query succeeded.See above for details.Otherwise, you can get an error if you e.g. drop an index (since it already doesn't exist in tables.sql because you just removed it). For extension patches, use the extension's equivalent of these files.Users can then update their wiki by running update.php. See Terms of Use for details. The main difference is that it is not computerized, so all the records and database itself are tangible. Practically manual databases are file boxes full or paper records and folders. Manual databases are still used in some smaller libraries and also in places where client register is needed for example hospitals. Most popular ways of organization are alphabetically, chronologically and numerically. The main purpose of the organization of manual database is to make all the order transparent, so the way of organization depends on the purpose of the database. Very large databases for example library databases also are organized by sections of themes and files in each section is organized by methods mentioned above. If you have understood that, all the following work is easy. For example, if records are organized alphabetically by authors, start searching from the letter of authors’ surname. Of course, usage of manual database is more complicated than usage of electronic database, because, you need to go through records by yourself. Manual databases don’t update automatically, so once in a while the cleaning of records is needed. All the unnecessary records have to be thrown out. If the database consists of huge amount of files, there can be a situation when database consists of useless files. That can encumber searching of records. Of course, manual databases needs a lot more space as well. That is because it takes a lot of time, work and money to computerize all the file system. For example, to computerize file system of hospitals, there is united system in whole country needed and that means millions of records must be digitalized. However lot of countries has done that and many are planning to do that. You never know, when that can turn out useful. Types of information systems. A separate set of instructions is available for each supported database.It is known to work without any security flaws. Users should be aware that there are known security issues if using some of the other encodings.For a Zabbix proxy database, only schema.sql should be imported (no images.sql nor data.sql):The following shell command will create user zabbix. Specify password when prompted and repeat password (note, you may first be asked for sudo password):For a Zabbix proxy database, only schema.sql should be imported (no images.sql nor data.sql).Check current settings. If you need further assistance, please contact your IT Department or do an internet search for your specific version of Office on ways to view hidden text. If you need further assistance, please contact your IT Department or do an internet search for your specific version of Office on ways to view hidden text. Instead, data managers are encouraged to use their institution’s medication guide or software. Any updates to the list are likely to occur with version upgrades. If changes occur prior to an update, sites and vendors will be notified. External Tables Scheduled Queries Exchange Partition Browse pages Configure Space tools Its recommended that MANAGEDLOCATION be within metastore.warehouse.dir so all managed tables have a common root where common governance policies. It can be used with metastore.warehouse.tenant.colocation to have it point to a directory outside the warehouse root directory to have a tenant based common root where quotas and other policies can be set. Drop Database To drop the tables in the database as well, use DROP DATABASE. CASCADE. Support for RESTRICT and CASCADE was added in Hive 0.8 ( HIVE-2090 ). Alter Database SET LOCATION statement does not move the contents of the database's current directory to the newly specified location. It only changes the default parent-directory where new tables will be added for this database. This behaviour is analogous to how changing a table-directory does not move existing partitions to a different location. The ALTER DATABASE. SET MANAGEDLOCATION statement does not move the contents of the database's managed tables directories to the newly specified location. No other metadata about a database can be changed. Use Database An error is thrown if a table or view with the same name already exists. You can use IF NOT EXISTS to skip the error. Backtick quotation also enables the use of reserved keywords for table and column identifiers. To revert to pre-0.13.0 behavior and restrict column names to alphanumeric and underscore characters, set the configuration property hive.support.quoted.identifiers to none. In this configuration, backticked names are interpreted as regular expressions. For details, see Supporting Quoted Identifiers in Column Names. Table and column comments are string literals (single-quoted). A table created without the EXTERNAL clause is called a managed table because Hive manages its data. As of Hive 2.4.0 ( HIVE-16324 ) the value of the property 'EXTERNAL' is parsed as a boolean (case insensitive true or false) instead of a case sensitive string comparison. See Alter Table below for more information about table comments, table properties, and SerDe properties. See Type System and Hive Data Types for details about the primitive and complex data types. Managed and External Tables By default Hive creates managed tables, where files, metadata and statistics are managed by internal Hive processes. For details on the differences between managed and external table see Managed vs. External Tables. Storage Formats Hive supports built-in and custom-developed file formats. See CompressedStorage for details on compressed table storage. The following are some of the formats built-in to Hive: Storage Format Description STORED AS TEXTFILE Stored as plain text files. TEXTFILE is the default file format, unless the configuration parameter hive.default.fileformat has a different setting. Use the DELIMITED clause to read delimited files. Enable escaping for the delimiter characters by using the 'ESCAPED BY' clause (such as ESCAPED BY '\') Escaping is needed if you want to work with data that can contain these delimiter characters. A custom NULL format can also be specified using the 'NULL DEFINED AS' clause (default is '\N'). STORED AS SEQUENCEFILE Stored as compressed Sequence File. STORED AS ORC Stored as ORC file format. Stores column-level metadata. STORED AS PARQUET Stored as Parquet format for the Parquet columnar storage format in Hive 0.13.0 and later; Use ROW FORMAT SERDE.STORED AS RCFILE Stored as Record Columnar File format. STORED AS JSONFILE Stored as Json file format in Hive 4.0.0 and later. STORED BY Stored by a non-native table format. To create or link to a non-native table, for example a table backed by HBase or Druid or Accumulo. See StorageHandlers for more information on this option. For example, 'org.apache.hadoop.hive.contrib.fileformat.base64.Base64TextInputFormat'. A native SerDe is used if ROW FORMAT is not specified or ROW FORMAT DELIMITED is specified. Use the SERDE clause to create a table with a custom SerDe. For more information on SerDes see: Hive SerDe SerDe HCatalog Storage Formats You must specify a list of columns for tables that use a native SerDe. Refer to the Types part of the User Guide for the allowable column types. A list of columns for tables that use a custom SerDe may be specified but Hive will query the SerDe to determine the actual list of columns for this table. For general information about SerDes, see Hive SerDe in the Developer Guide. Also see SerDe for details about input and output processing. The following example defines a table in the default Apache Weblog format. JSON ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe' STORED AS TEXTFILE Stored as plain text file in JSON format. It was added to the Hive distribution by HIVE-4895. The CSVSerde is available in Hive 0.14 and greater. The following example creates a TSV (Tab-separated) file. To use the SerDe, specify the fully qualified class name org.apache.hadoop.hive.serde2.OpenCSVSerde. Documentation is based on original documentation at. Limitations This SerDe treats all columns to be of type String. Even if you create a table with non-string column types using this SerDe, the DESCRIBE TABLE output would show string column type. The type information is retrieved from the SerDe. To convert columns to the desired type in a table, you can create a view over the table that does the CAST to the desired type. The CSV SerDe is based on, and was added to the Hive distribution in HIVE-7777. The CSVSerde has been built and tested against Hive 0.14 and later, and uses Open-CSV 2.3 which is bundled with the Hive distribution. Partitioned Tables Partitioned tables can be created using the PARTITIONED BY clause. A table can have one or more partition columns and a separate data directory is created for each distinct value combination in the partition columns. Further, tables or partitions can be bucketed using CLUSTERED BY columns, and data can be sorted within that bucket via SORT BY columns. This can improve performance on certain kinds of queries. You probably really do have the column defined. However, the partition you create makes a pseudocolumn on which you can query, so you must rename your table column to something else (that users should not query on!). For example, suppose your original unpartitioned table had three columns: id, date, and name. Example: The data format in the files is assumed to be field-delimited by ctrl-A and row-delimited by newline. Example: Specify a value for the key hive.metastore.warehouse.dir in the Hive config file hive-site.xml. External Tables The EXTERNAL keyword lets you create a table and provide a LOCATION so that Hive does not use a default location for this table. This comes in handy if you already have data generated. When dropping an EXTERNAL table, data in the table is NOT deleted from the file system. Starting Hive 4.0.0 (For another example of creating an external table, see Loading Data in the Tutorial. Create Table As Select (CTAS) Tables can also be created and populated by the results of a query in one create-table-as-select (CTAS) statement. The table created by CTAS is atomic, meaning that the table is not seen by other users until all the query results are populated. So other users will either see the table with the complete results of the query or will not see the table at all. There are two parts in CTAS, the SELECT part can be any SELECT statement supported by HiveQL. The CREATE part of the CTAS takes the resulting schema from the SELECT part and creates the target table with other table properties such as the SerDe and storage format. Starting with Hive 3.2.0, CTAS statements can define a partitioning specification for the target table ( HIVE-20241 ). CTAS has these restrictions: The target table cannot be an external table. The target table cannot be a list bucketing table. Example: Starting with Hive 0.13.0, the SELECT statement can include one or more common table expressions (CTEs), as shown in the SELECT syntax. For an example, see Common Table Expression. Being able to select data from one table to another is one of the most powerful features of Hive. Hive handles the conversion of the data from the source format to the destination format as the query is being executed. Create Table Like The LIKE form of CREATE TABLE allows you to copy an existing table definition exactly (without copying its data). The new table contains no rows. The sorting property allows internal operators to take advantage of the better-known data structure while evaluating queries, also increasing efficiency. MAP KEYS and COLLECTION ITEMS keywords can be used if any of the columns are lists or maps. This means that users must be careful to insert data correctly by specifying the number of reducers to be equal to the number of buckets, and using CLUSTER BY and SORT BY commands in their query. There is also an example of creating and populating bucketed tables. Skewed Tables Version information As of Hive 0.10.0 ( HIVE-3072 and HIVE-3649 ). See HIVE-3026 for additional JIRA tickets that implemented list bucketing in Hive 0.10.0 and 0.11.0. Design documents Read the Skewed Join Optimization and List Bucketing design documents for more information. This feature can be used to improve performance for tables where one or more columns have skewed values. By specifying the values that appear very often (heavy skew) Hive will split those out into separate files (or directories in case of list bucketing ) automatically and take this fact into account during queries so that it can skip or include the whole file (or directory in case of list bucketing ) if possible. This can be specified on a per-table level during table creation. The following example shows one column with three skewed values, optionally with the STORED AS DIRECTORIES clause which specifies list bucketing. Example: Data will be stored in the user's scratch directory, and deleted at the end of the session. The user will not be able to access the original table within that session without either dropping the temporary table, or renaming it to a non-conflicting name. Temporary tables have the following limitations: Partition columns are not supported. No support for creation of indexes. S tarting in Hive 1.1.0 t he storage policy for temporary tables can be set to memory, ssd, or default with the hive.exec.temporary.table.storage configuration parameter (see HDFS Storage Types and Storage Policies ). Example: See this for more details about transactional tables. Example: Some SQL tools generate more efficient queries when constraints are present. Since these constraints are not validated, an upstream system needs to ensure data integrity before it is loaded into Hive. Example: Hive includes support for UNIQUE, NOT NULL, DEFAULT and CHECK constraints. Beside UNIQUE all three type of constraints are enforced. Example: Drop Table The metadata is completely lost. When dropping an EXTERNAL table, data in the table will NOT be deleted from the file system. Starting Hive 4.0.0 (Otherwise, the table information is removed from the metastore and the raw data is removed as if by 'hadoop dfs -rm'. In many cases, this results in the table data being moved into the user's.Trash folder in their home directory; users who mistakenly DROP TABLEs may thus be able to recover their lost data by recreating a table with the same schema, recreating any necessary partitions, and then moving the data back into place manually using Hadoop. This solution is subject to change over time or across installations as it relies on the underlying implementation; users are strongly encouraged not to drop tables capriciously. The purge option can also be specified with the table property auto.purge (see TBLPROPERTIES above). In Hive 0.7.0 or later, DROP returns an error if the table doesn't exist, unless IF EXISTS is specified or the configuration variable hive.exec.drop.ignorenonexistent is set to true. See the Alter Partition section below for how to drop partitions. Truncate Table Version information As of Hive 0.11.0 ( HIVE-446 ). This is applicable only for managed tables (see managed tables ). Starting with Hive 4.0 ( HIVE-23183 ) the TABLE token is optional, previous versions required it.Similarly, alter table partition statements allow you change the properties of a specific partition in the named table. Alter Table Rename Table As of version 0.6, a rename on a managed table moves its HDFS location. Rename has been changed as of version 2.2.0 ( HIVE-14909 ) so that a managed table's HDFS location is moved only if the table is created without a LOCATION clause and under its database directory. Hive versions prior to 0.6 just renamed the table in the metastore without moving the HDFS location. Alter Table Properties Users can add their own properties to this list. You can do DESCRIBE EXTENDED TABLE to get this information. For more information, see the TBLPROPERTIES clause in Create Table above. Alter Table Comment To change the comment of a table you have to change the comment property of the TBLPROPERTIES: The SerDe properties are passed to the table's SerDe when it is being initialized by Hive to serialize and deserialize data. So users can store any information required for their custom SerDe here.NOTE: These commands will only modify Hive's metadata, and will NOT reorganize or reformat existing data. Users should make sure the actual data layout conforms with the metadata definition. Alter Table Skewed or Stored as Directories Version information As of Hive 0.10.0 ( HIVE-3072 and HIVE-3649 ). See HIVE-3026 for additional JIRA tickets that implemented list bucketing in Hive 0.10.0 and 0.11.0. A table's SKEWED and STORED AS DIRECTORIES options can be changed with ALTER TABLE statements. Alter Table Skewed Alter Table Not Skewed This affects partitions created after the ALTER statement, but has no effect on partitions created before the ALTER statement. Alter Table Not Stored as Directories Alter Table Set Skewed Location Alter Table Constraints Version information As of Hive release 2.1.0. Table constraints can be added or removed via ALTER TABLE statements. Alter Partition Partitions can be added, renamed, exchanged (moved), dropped, or (un)archived by using the PARTITION clause in an ALTER TABLE statement, as described below. To make the metastore aware of partitions that were added directly to HDFS, you can use the metastore check command ( MSCK ) or on Amazon EMR you can use the RECOVER PARTITIONS option of ALTER TABLE. The values can be number literals. Add Partitions Partition values should be quoted only if they are strings. The location must be a directory inside of which data files reside. (ADD PARTITION changes the table metadata, but does not load data. That is, every query specifying a partition will always use only the first partition.See these documents for details and examples: Design Document for Dynamic Partitions Tutorial: Dynamic-Partition Insert Hive DML: Dynamic Partition Inserts HCatalog Dynamic Partitioning Usage with Pig Usage from MapReduce Rename Partition Version information As of Hive 0.9. One of use cases is that you can use this statement to normalize your legacy partition column value to conform to its type. Exchange Partition Partitions can be exchanged (moved) between tables.For further details on this feature, see Exchange Partition and HIVE-4095. Discover Partitions Automatically discovers and synchronizes the metadata of the partition in Hive Metastore. If the table is a transactional table, then Exclusive Lock is obtained for that table before performing msck repair. When a retention interval is specified, the background thread running in HMS (refer Discover Partitions section), will check the age (creation time) of the partition and if the partition's age is older than the retention period, it will be dropped. Dropping partitions after retention period will also delete the data in that partition. Version information As of Hive 4.0.0 ( HIVE-20707 ). Recover Partitions (MSCK REPAIR TABLE) Hive stores a list of partitions for each table in its metastore. However, users can run a metastore check command with the repair table option: The default option for MSC command is ADD PARTITIONS. With this option, it will add any partitions that exist on HDFS but not in metastore to the metastore. The DROP PARTITIONS option will remove the partition information from metastore, that is already removed from HDFS. The SYNC PARTITIONS option is equivalent to calling both ADD and DROP PARTITIONS. See HIVE-874 and HIVE-17824 for more details. When there is a large number of untracked partitions, there is a provision to run MSCK REPAIR TABLE batch wise to avoid OOME ( Out of Memory Error). By giving the configured batch size for the property hive.msck.repair.batch.size it can run in the batches internally. The default value of the property is zero, it means it will execute all the partitions at once. MSCK command without the REPAIR option can be used to find details about metadata mismatch metastore. The equivalent command on Amazon Elastic MapReduce (EMR)'s version of Hive is: Drop Partitions This removes the data and metadata for this partition. Version Information: PROTECTION IGNORE PROTECTION is no longer available in versions 2.0.0 and later. This functionality is replaced by using one of the several security options available with Hive (see SQL Standard Based Hive Authorization ). See HIVE-11145 for details.Note that only the file count will be reduced; HAR does not provide any compression.The operation only changes the table metadata. Any conversion of existing data must be done outside of Hive.Since the script modifies files outside of hive, the modification wouldn't be logged by the hook. The external script could call TOUCH to fire the hook and mark the said table or partition as modified. Also, it may be useful later if we incorporate reliable last modified times. Then touch would update that time as well. See HIVE-11145 for details. Enabling OFFLINE prevents the data in a table or partition from being queried, but the metadata can still be accessed. As of Hive release 1.3.0 and 2.1.0 when transactions are being used, the ALTER TABLE. COMPACT statement can include a TBLPROPERTIES clause that is either to change compaction MapReduce job properties or to overwrite any other Hive table properties. More details can be found here. However, if compaction is turned off for a table or you want to compact the table at a time the system would not choose to, ALTER TABLE can initiate the compaction. By default the statement will enqueue a request for compaction and return. To watch the progress of the compaction, use SHOW COMPACTIONS. See the Basic Design section in Hive Transactions for more information. In Hive release 0.14.0 ORC files added support fast stripe level merging of small ORC files using concatenate command. In case of RCFile the merge happens at block level whereas for ORC files the merge happens at stripe level thereby avoiding the overhead of decompressing and decoding the data.For example when a user creates an Avro stored table using a schema url or schema literal, the schema will be inserted into HMS and then will never be changed in HMS regardless of url or literal changes within the serde. This can lead to problems especially when integrating with other Apache components. The update columns feature provides a way for the user to let any schema changes made in the serde to be synced into HMS. It works on both the table and the partitions levels, and obviously only for tables whose schema is not tracked by HMS (see metastore.serdes.using.metastore.for.schema). Using the command on these latter serde types will result in error. Alter Column Rules for Column Names Column names are case insensitive. Version information In Hive release 0.12.0 and earlier, column names can only contain alphanumeric and underscore characters. See Supporting Quoted Identifiers in Column Names for details. Backtick quotation enables the use of reserved keywords for column names, as well as table names.The PARTITION clause is available in Hive 0.14.0 and later; see Upgrading Pre-Hive 0.13.0 Decimal Columns for usage. A patch for Hive 0.13 is also available (see HIVE-7971 ). RESTRICT is the default, limiting column change only to table metadata. ALTER TABLE CHANGE COLUMN CASCADE clause will override the table partition's column metadata regardless of the table or partition's protection mode. Use with discretion. The column change command will only modify Hive's metadata, and will not modify data.This is supported for Avro backed tables as well, for Hive 0.14 and later. REPLACE COLUMNS removes all existing columns and adds the new set of columns. This can be done only for tables with a native SerDe (DynamicSerDe, MetadataTypedColumnsetSerDe, LazySimpleSerDe and ColumnarSerDe).