HIVE: Data Warehousing & Analytics on Hadoop
•Als PPT, PDF herunterladen•
142 gefällt mir•111,180 views
Hive is a data warehousing system built on Hadoop that allows users to query data using SQL. It addresses issues with using Hadoop for analytics like programmability and metadata. Hive uses a metastore to manage metadata and supports structured data types, SQL queries, and custom MapReduce scripts. At Facebook, Hive is used for analytics tasks like summarization, ad hoc analysis, and data mining on over 180TB of data processed daily across a Hadoop cluster.
![Why Another Data Warehousing System? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Empfohlen
Empfohlen
Weitere ähnliche Inhalte
Was ist angesagt?
Was ist angesagt? (20)
Andere mochten auch
Andere mochten auch (18)
Ähnlich wie HIVE: Data Warehousing & Analytics on Hadoop
Ähnlich wie HIVE: Data Warehousing & Analytics on Hadoop (20)
Kürzlich hochgeladen
Kürzlich hochgeladen (20)
HIVE: Data Warehousing & Analytics on Hadoop
- 1. HIVE Data Warehousing & Analytics on Hadoop Facebook Data Team
- 4. Data Warehousing at Facebook Today Web Servers Scribe Servers Filers Hive on Hadoop Cluster Oracle RAC Federated MySQL
- 7. HIVE: Components HDFS Hive CLI DDL Queries Browsing Map Reduce MetaStore Thrift API SerDe Thrift Jute JSON.. Execution Hive QL Parser Planner Mgmt. Web UI
- 8. Data Model Logical Partitioning Hash Partitioning Schema Library clicks HDFS MetaStore / hive/clicks /hive/clicks/ds=2008-03-25 /hive/clicks/ds=2008-03-25/0 … Tables #Buckets=32 Bucketing Info Partitioning Cols
- 13. (Simplified) Map Reduce Review Machine 2 Machine 1 <k1, v1> <k2, v2> <k3, v3> <k4, v4> <k5, v5> <k6, v6> <nk1, nv1> <nk2, nv2> <nk3, nv3> <nk2, nv4> <nk2, nv5> <nk1, nv6> Local Map <nk2, nv4> <nk2, nv5> <nk2, nv2> <nk1, nv1> <nk3, nv3> <nk1, nv6> Global Shuffle <nk1, nv1> <nk1, nv6> <nk3, nv3> <nk2, nv4> <nk2, nv5> <nk2, nv2> Local Sort <nk2, 3> <nk1, 2> <nk3, 1> Local Reduce
- 15. Hive QL – Join in Map Reduce page_view user pv_users Map Shuffle Sort Reduce key value 111 < 1, 1> 111 < 1, 2> 222 < 1, 1> pageid userid time 1 111 9:08:01 2 111 9:08:13 1 222 9:08:14 userid age gender 111 25 female 222 32 male key value 111 < 2, 25> 222 < 2, 32> key value 111 < 1, 1> 111 < 1, 2> 111 < 2, 25> key value 222 < 1, 1> 222 < 2, 32> pageid age 1 25 2 25 pageid age 1 32
- 20. Hive QL – Group By in Map Reduce pv_users Map Shuffle Sort Reduce pageid age 1 25 2 25 pageid age count 1 25 1 1 32 1 pageid age 1 32 2 25 key value <1,25> 1 <2,25> 1 key value <1,32> 1 <2,25> 1 key value <1,25> 1 <1,32> 1 key value <2,25> 1 <2,25> 1 pageid age count 2 25 2
- 22. Hive QL – Group By with Distinct in Map Reduce page_view Shuffle and Sort Reduce Map Reduce pageid count 1 1 2 1 pageid count 1 1 pageid userid time 1 111 9:08:01 2 111 9:08:13 pageid userid time 1 222 9:08:14 2 111 9:08:20 key v <1,111> <2,111> <2,111> key v <1,222> pageid count 1 2 pageid count 2 1
Hinweis der Redaktion
- STYLE GUIDELINES The master cannot be changed, if you are going to place another logo on any slide, please place it in the lower right corner. Title sizes may not be tampered with. If your title is too long please shorten it. Please do not center the title and subtitle, everything is made to align with the Facebook logo above them. Always remember to use the correct slide type for what you’re using it for. If you’re looking to use half a slide with bullet points and the other half with a picture, pick the correct slide type.