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The "Hbase/DesignOverview" page has been changed by DougMeil. The comment on this change is: Per stack, this page is now directing readers to the HBase book.. http://wiki.apache.org/hadoop/Hbase/DesignOverview?action=diff&rev1=21&rev2=22 -------------------------------------------------- - '''This page was created on 06.03.09 and now is in progress of construction....''' - = Table of Contents = + The HBase design overview can now be found in the HBase book at [[http://hbase.apache.org/book.html#datamodel]] - * [[#intro|Introduction]] - * [[#datamodel|Data Model]] - * [[#conceptual|Conceptual View]] - * [[#internal|Internal View]] - * [[#api|API]] - * [[#design|Architecture Design]] - * [[#master|HBaseMaster]] - * [[#hregionserv|HRegionServer]] - * [[#client|HBase Client]] - * [[#impl|Implementation]] - <<Anchor(intro)>> - = Introduction = - This paper is HBase oriented analogue of Google [[http://labs.google.com/papers/bigtable.html|Bigtable paper]]. This paper will be self-sufficient. - - HBase is an [[http://apache.org/|Apache]] open source project whose goal is to provide Bigtable-like storage for the Hadoop Distributed Computing Environment. HBase leverages the distributed data storage provided by the [[http://hadoop.apache.org/core/docs/current/hdfs_design.html|Hadoop Distributed File System (HDFS)]] and use [[http://hadoop.apache.org/zookeeper/docs/current/zookeeperOver.html|ZooKeeper]] for coordination between HBase nodes. - - Data is logically organized into tables, rows and columns. An iterator-like interface is available for scanning through a row range and, of course, there is the ability to retrieve a column value for a specific row key. Any particular column may have multiple versions for the same row key. - - <<Anchor(datamodel)>> - = Data Model = - - Applications store data rows in labeled tables. A data row has a sortable row key and an arbitrary number of columns. The table is stored sparsely, so that rows in the same table can have widely varying numbers of columns. - - HBase table is three dimensional sorted map. It maps from Cartesian product of row key, column key and timestamp to cell value: - - '''(row:byte[] x column:byte[] x timestamp:Long) -> byte[]''' - - A column name has the form ''"<family>:<label>"'' where <family> and <label> can be arbitrary byte arrays. A table enforces its set of <family>s (called ''"column families"''). Adjusting the set of families is done by performing administrative operations on the table. However, new <label>s can be used in any write operation without pre-announcing it. HBase stores column families physically close on disk, so the items in a given column family should have roughly the same read/write characteristics and contain similar data. - - Only a single row at a time may be locked by default. Row writes are always atomic, but it is also possible to lock a single row and perform both read and write operations on that row atomically. - - An extension was added recently to allow multi-row locking, but this is not the default behavior and must be explicitly enabled. - - More details are here [[Hbase/DataModel| The HBase Data Model]] - - <<Anchor(conceptual)>> - == Conceptual View == - - Conceptually a table may be thought of a collection of rows that are located by a row key (and optional timestamp) and where any column - may not have a value for a particular row key (sparse). - - <<Anchor(datamodelexample)>> - ||<:> '''Row Key''' ||<:> '''Time Stamp''' ||<:> '''Column''' ''"contents:"'' ||||<:> '''Column''' ''"anchor:"'' ||<:> '''Column''' ''"mime:"'' || - ||<^|5> "com.cnn.www" ||<:> t9 || ||<)> "anchor:cnnsi.com" ||<:> "CNN" || || - ||<:> t8 || ||<)> "anchor:my.look.ca" ||<:> "CNN.com" || || - ||<:> t6 ||<:> "<html>..." || || ||<:> "text/html" || - ||<:> t5 ||<:> "<html>..." || || || || - ||<:> t3 ||<:> "<html>..." || || || || - - <<Anchor(internal)>> - == Internal View == - - Although at a conceptual level, tables may be viewed as a sparse set of rows, physically they are stored on a per-column family basis. This is an important consideration for schema and application designers to keep in mind. - - Pictorially, the table shown in the [[#datamodelexample|conceptual view]] above would be stored as follows: - - ||<:> '''Row Key''' ||<:> '''Time Stamp''' ||<:> '''Column''' ''"contents:"'' || - ||<^|3> "com.cnn.www" ||<:> t6 ||<:> "<html>..." || - ||<:> t5 ||<:> "<html>..." || - ||<:> t3 ||<:> "<html>..." || - - <<BR>> - - ||<:> '''Row Key''' ||<:> '''Time Stamp''' |||| '''Column''' ''"anchor:"'' || - ||<^|2> "com.cnn.www" ||<:> t9 ||<)> "anchor:cnnsi.com" ||<:> "CNN" || - ||<:> t8 ||<)> "anchor:my.look.ca" ||<:> "CNN.com" || - - <<BR>> - - ||<:> '''Row Key''' ||<:> '''Time Stamp''' ||<:> '''Column''' ''"mime:"'' || - || "com.cnn.www" ||<:> t6 ||<:> "text/html" || - - <<BR>> - - It is important to note in the diagram above that the empty cells shown in the conceptual view are not stored since they need not be in a column-oriented storage format. Thus a request for the value of the ''"contents:"'' column at time stamp t8 would return no value. Similarly, a request for an ''"anchor:my.look.ca"'' value at time stamp t9 would return no value. - - However, if no timestamp is supplied, the most recent value for a particular column would be returned and would also be the first one found since timestamps are stored in descending order. Thus a request for the values of all columns in the row "com.cnn.www" if no timestamp is specified would be: the value of ''"contents:"'' from time stamp t6, the value of ''"anchor:cnnsi.com"'' from time stamp t9, the value of ''"anchor:my.look.ca"'' from time stamp t8 and the value of ''"mime:"'' from time stamp t6. - - === Regions (Row Ranges) === - - To an application, a table appears to be a list of tuples sorted by row key ascending, column name ascending and timestamp descending. Physically, tables are broken up into row ranges called ''regions''. Each row range contains rows from start-key (inclusive) to end-key (exclusive). A set of regions, sorted appropriately, forms an entire table. Row range identified by the table name and start-key. - - Each column family in a region is managed by an ''Store''. Each ''Store'' may have one or more ''!StoreFiles'' (a Hadoop HDFS file type). !StoreFiles are immutable once closed. !StoreFiles are stored in the Hadoop HDFS. Other details: - * !StoreFiles cannot currently be mapped into memory. - * !StoreFiles maintain the sparse index in a separate file - * HBase extends !StoreFiles so that a bloom filter can be employed to enhance negative lookup performance. The hash function employed is one developed by Bob Jenkins. - - <<Anchor(api)>> - = API = - - == Client API == - - See the Javadoc for [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/HTable.html|HTable]] and [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/HBaseAdmin.html|HBaseAdmin]] - - == Scanner API == - - To obtain a scanner, a Cursor-like row 'iterator' that must be closed, [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/HTable.html#HTable(org.apache.hadoop.hbase.HBaseConfiguration,%20java.lang.String)|instantiate an HTable]], and then invoke ''getScanner''. This method returns an [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/Scanner.html|Scanner]] against which you call [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/Scanner.html#next()|next]] and ultimately [[http://hadoop.apache.org/hbase/docs/current/api/org/apache/hadoop/hbase/client/Scanner.html#close()|close]]. - - <<Anchor(design)>> - = Architecture Design = - - HBase has Multiple Client - Multiple Server Client-Server architecture. - - There are three major components of the HBase architecture: - 1. The HMaster (HBase master server) - 2. The H!RegionServer (HBase region server) - 3. The HBase client, defined by org.apache.hadoop.hbase.client.HTable - - Each will be discussed in the following sections. - - <<Anchor(master)>> - == HMaster == - - There is only one HMaster for a single HBase deployment. To ensure that there is always one active HMaster uses [[http://hadoop.apache.org/zookeeper/docs/current/recipes.html#sc_leaderElection|leader election algorithm]] and it's address is stored in !ZooKeaper. - - If HMaster dies, starts new competition between not active "hot ready" HMasters using [[http://hadoop.apache.org/zookeeper/docs/current/recipes.html#sc_leaderElection|leader election algorithm]]. - - HMaster duties: - - * Cluster initialization - * Assigning/unassigning regions to/from H!RegionServers (unassigning is for load balance) - * Monitor the health and load of each H!RegionServer - * Changes to the table schema and handling table administrative functions - * Data localization - - == Cluster initialization == - - While first start master tries to get root and root region directories from HDFS and after fail creates them and first meta region directory. In next start master will get information about cluster and it's regions. - - === Assigning regions to HRegionServers === - - Each region is assigned to only one H!RegionServer or not assigned yet. The first region to be assigned is the ''ROOT region'' which locates all the META regions to be assigned. Each ''META region'' maps a number of user regions which comprise the multiple tables that a particular HBase instance serves. Once all the META regions have been assigned, the master will then assign user regions to the H!RegionServers, attempting to balance the number of regions served by each H!RegionServer. - - ==== Assigned region ==== - - If region is assigned to some H!RegionServer it means that this region served by this server. While serving region H!RegionServer handles read/write requests to this region, caches last (not yet flushed) modifications in Memcache and writes all changes to WAL but persistent reliable storage of regions is provided by HDFS. - - ==== The META Table ==== - - The META table stores information about every user region in HBase which includes a H!RegionInfo object containing information such as HRegion id, start and end keys, a reference to this HRegions' table descriptor, etc. and the address of the H!RegionServer that is currently serving the region. The META table can grow as the number of user regions grows. - - ==== The ROOT Table ==== - - The ROOT table is confined to a single region and maps all the regions in the META table. Like the META table, it contains a H!RegionInfo object for each META region and the location of the H!RegionServer that is serving that META region. - - Each row in the ROOT and META tables is approximately 1KB in size. At the default region size of 256MB, this means that the ROOT region can map 2.6 x 10^5^ META regions, which in turn map a total 6.9 x 10^10^ user regions, meaning that approximately 1.8 x 10^19^ (2^64^) bytes of user data. - - Every server (master or region) can get ''ROOT region'' location from !ZooKeeper. - - === Monitor the health of each HRegionServer === - - If HMaster detects a H!RegionServer is no longer reachable, it will split the H!RegionServer's write-ahead log so that there is now one write-ahead log for each region that the H!RegionServer was serving. After it has accomplished this, it will reassign the regions that were being served by the unreachable H!RegionServer. - - If HMaster detects overloaded or low loaded H!RegionServer, it will unassign (close) some regions from most loaded H!RegionServer. Unassigned regions will be assigned to low loaded servers. - - === Changes to the table schema and handling table administrative functions === - - Table schema is set of tables and it's column families. HMaster can add and remove column families, turn on/off tables. - - == Data localization == - - Clients can request location of regions to read data directly from region servers. - - <<Anchor(hregionserv)>> - == HRegionServer == - - H!RegionServer duties: - - * Serving HRegions assigned to H!RegionServer - * Handling client read and write requests - * Flushing cache to HDFS - * Keeping HLog - * Compactions - * Region Splits - - === Serving HRegions assigned to HRegionServer === - - Each HRegion is served by only one H!RegionServer. When H!RegionServer starts serving HRegion, it reads HLog and all !StoreFiles from HDFS for this HRegion. While serving HRegions, H!RegionServer manage persistent storage of all changes to HDFS. - - === Handling client read and write requests === - - Client communicates with the HMaster to get a list of HRegions and H!RegionServers serving them. Then client sends write/read requests directly to H!RegionServers. - - ==== Write Requests ==== - - When a write request is received, it is first written to a write-ahead log called a ''HLog''. All write requests for every region the region server is serving are written to the same ''HLog''. Once the request has been written to the ''HLog'', the result of changes is stored in an in-memory cache called the ''Memcache''. There is one Memcache for each Store. - - ==== Read Requests ==== - - Reads are handled by first checking the Memcache and if the requested data is not found, the !StoreFiles are searched for results. - - === Cache Flushes === - - When the Memcache reaches a configurable size, it is flushed to HDFS, creating a new !StoreFile and a marker is written to the HLog, so that when it is replayed, log entries before the last flush can be skipped. A flush may also be triggered to relieve memory pressure on the region server. - - Cache flushes happen concurrently with the region server processing read and write requests. Just before the new !StoreFile is moved into place, reads and writes are suspended until the !StoreFile has been added to the list of active !StoreFile for the HStore. - - === Keeping HLog === - - There is only one ''HLog'' per each H!RegionServer. It is write-ahead log for all changes in serving HRegions for this server. - - There are 2 processes that restricts ''HLog'' size: - * Rolling process: when ''HLog'' file reaches a configurable size, ''HLog'' starts to write in new file and closes old one. - * Flushing process: when ''HLog'' reaches a configurable size, it is flushed to HDFS. - - === Compactions === - - When the number of !StoreFiles exceeds a configurable threshold, a minor compaction is performed which consolidates the most recently written !StoreFiles. A major compaction is performed periodically which consolidates all the !StoreFiles into a single !StoreFile. The reason for not always performing a major compaction is that the oldest !StoreFile can be quite large and reading and merging it with the latest !StoreFiles, which are much smaller, can be very time consuming due to the amount of I/O involved in reading merging and writing the contents of the largest !StoreFile. - - Compactions happen concurrently with the region server processing read and write requests. Just before the new !StoreFile is moved into place, reads and writes are suspended until the !StoreFile has been added to the list of active !StoreFiles for the HStore and the !StoreFiles that were merged to create the new !StoreFile have been removed. - - === Region Splits === - - When the aggregate size of the !MapFiles for an HStore reaches a configurable size (currently 256MB), a region split is requested. Region splits divide the row range of the parent region in half and happen very quickly because the child regions read from the parent's !MapFile. - - The parent region is taken off-line, the region server records the new child regions in the META region and the master is informed that a split has taken place so that it can assign the children to region servers. Should the split message be lost, the master will discover the split has occurred since it periodically scans the META regions for unassigned regions. - - Once the parent region is closed, read and write requests for the region are suspended. The client has a mechanism for detecting a region split and will wait and retry the request when the new children are on-line. - - When a compaction is triggered in a child, the data from the parent is copied to the child. When both children have performed a compaction, the parent region is garbage collected. - - <<Anchor(client)>> - == HBase Client == - - HBase is a Heavy Client System. Each client manages its own connection to appropriate server. - - The HBase client is responsible for finding H!RegionServers that are serving the particular row range of interest. On instantiation, the HBase client communicates with the H!BaseMaster to find the location of the ROOT region. This is the only communication between the client and the master. - - Once the ROOT region is located, the client contacts that region server and scans the ROOT region to find the META region that will contain the location of the user region that contains the desired row range. It then contacts the region server that is serving that META region and scans that META region to determine the location of the user region. - - After locating the user region, the client contacts the region server serving that region and issues the read or write request. - - This information is cached in the client so that subsequent requests need not go through this process. - - Should a region be reassigned either by the master for load balancing or because a region server has died, the client will rescan the META table to determine the new location of the user region. If the META region has been reassigned, the client will rescan the ROOT region to determine the new location of the META region. If the ROOT region has been reassigned, the client will contact the master to determine the new ROOT region location and will locate the user region by repeating the original process described above. - - <<Anchor(impl)>> - = Implementation = - Here will be details of HBase implementation. -
