stream processing

high performance

Scalable

High fault tolerance

Generate files directly according to the source file name

Set the file generation time interval, close the old file when the time interval is reached, and the new data will be written to the new file

Set the size of a single file, when the file size reaches the set value, the old file will be closed, and the new data will be written to the new file

Set up single file storageeventquantity, when the file is storedeventWhen the number reaches the set value, the old file will be closed, and the new data will be

is written to a new file

hive.exec.compress.intermediate

hive.intermediate.compression.codec

hive.exec.compress.output

hive.intermediate.compression.type

mouthJDB, Cinterface

mouthODB, Cinterface

mouthPythoninterface

mouthRubyinterface

True

False

True

False

Attribute values with high access weight are placed inRowKeyFront

Attribute values with high access weight are placed inRowkeysecond half

Attribute values with good dispersion are placed inRowkeyfirst half

Attribute values with good dispersion are placed inRowkeysecond half

Table Name

Table names and column families(or table name andfamily)

table names and columns

can be empty

SolrUser group users can create configuration sets and createCollectionwhen specifying the configuration set

SolrUsers of the user group can createCollection

Collectioncreator, theCollectionroles with read and write permissions andSolr adminrole can beCollectionEnter

row update

onlyCollectioncreator andSolr adminRoles can be deletedCollection

clickClouddownTree,CheckSolr CloudmiddleCollections, a configuration set, andlive_nodesand other metadata information

clickCloud, see eachCollectionunder eachShardReplicadistribution and status

enter aCollectionofShard ReplicaofCore Overviewinterface, you can view theReplicaIndex the actual document

Number of bars, storage size and location information

Solruser group,Solr adminrole andSuper groupof users have access toSolr Admin UI

lines.flatMap(_.split??)).map(word= > (word,1)).reduce(_+_).print ( )

lines.flatMap(_.split??)).map(word= > (word,word.length())).reduceByKey(_+_).print ( )

lines.flatMap(_.split??)).map(word= > (word,1)).reduceByKey(_+_).print ( )

lines.flatMap(_.split??)).flatmap(word= > (word,1)).groupByKey(_+_).print ( )

Mass data storage

Lots of small file storage

large file storage

Streaming file storage