I'm trying to create tables pragmatically using JDBC. However, I can't really see the table I created from the hive shell. What's worse, when i access hive shell from different directories, i see different result of the database.
Is any setting i need to configure?
Thanks in advance.
Make sure you run hive from the same directory every time because when you launch hive CLI for the first time, it creates a metastore derby db in the current directory. This derby DB contains metadata of hive tables. If you change directories, you will have unorganized metadata for hive tables. Also the Derby DB cannot handle multiple sessions. To allow for concurrent Hive access you would need to use a real database to manage the Metastore rather than the wimpy little derbyDB that comes with it. You can download mysql for this and change hive properties for jdbc connection to mysql type 4 pure java driver.
Try emailing the Hive userlist or the IRC channel.
You probably need to setup the central Hive metastore (by default, Derby, but it can be mySQL/Oracle/Postgres). The metastore is the "glue" between Hive and HDFS. It tells Hive where your data files live in HDFS, what type of data they contain, what tables they belong to, etc.
For more information, see http://wiki.apache.org/hadoop/HiveDerbyServerMode
Examine your hadoop logs. For me this happened when my hadoop system was not setup properly. The namenode was not able to contact the datanodes on other machines etc.
Yeah, it's due to the metastore not being set up properly. Metastore stores the metadata associated with your Hive table (e.g. the table name, table location, column names, column types, bucketing/sorting information, partitioning information, SerDe information, etc.).
The default metastore is an embedded Derby database which can only be used by one client at any given time. This is obviously not good enough for most practical purposes. You, like most users, should configure your Hive installation to use a different metastore. MySQL seems to be a popular choice. I have used this link from Cloudera's website to successfully configure my MySQL metastore.
Related
Is Hive and Impala integration possible?
After data processing in hive i want to store result data in impala for better read, is it possible?
If yes can you please share one example.
Both hive and impala, do not store any data. The data is stored in the HDFS location and hive an impala both are used just to visualize/transform the data present in the HDFS.
So yes, you can process the data using hive and then read it using impala, considering both of them have been setup properly. But since impala needs to be refreshed, you need to run the invalidate metadata and refresh commands
Impala uses the HIVE metastore to read the data. Once you have a table created in hive, it is possible to read the same and query the same using Impala. All you need is to refresh the table or trigger INVALIDATE METADATA in impala to read the data.
Hope this helps :)
Hive and impala are two different query engines. Each query engine is unique in terms of its architecture as well as performance. We can use hive metastore to get metadata and running query using impala. The common usecase is to connect impala/hive from tableau. If we are visualizing hive from tableau, we can get the latest data without any work around. If we keep on loading the data continuously, metadata will be updated as well. Impala does not aware of those changes. So we should run metadata invalidate query by connecting impalad to refresh its state and sync with the latest info available in metastore. So that user will get the same results as hive when the run the same query from tableau using impala engine.
There is no configuration parameter available now to run this invalidation query periodically. This blog reads well to execute meta data invalidation query through oozie scheduler periodically to handle such problems, Or simply we can set up a cronjob from the server itself.
when using jupyter to cache some data into spark (using sqlcontext.cacheTable) i can see the table cached for the sparkcontext running within Jupyter. But now i want to access those cached tables from BI tools via odbc using the thrift server. when checking the thriftserver cache I dont see any table, the question is how do i get those tables cached to be consumed from BI tools?
do i have to send the same spark commands via jdbc? in that case, is the context related to the current session?
regards,
miguel
I found the solution. In order to have the tables cached to be used with jdbc/odbc clients via thriftserver i have to use CACHE TABLE from one of the clients, for exmaple from beeline. Once this is done the table is in-memory for all the different sessions.
It is also important to be sure you are using the right spark thriftserver. In order to know that just do a show table; in beeline, if you get just one column back you are not using the spark one and the CACHE TABLE wont work.
Hive installation guide says that Hive can be applied to RDBMS, my question is, sounds like Hive can exist without Hadoop, right? It's an independent HQL engineer that could work with any data source?
You can run Hive in local mode to use it without Hadoop for debugging purposes. See below url
https://cwiki.apache.org/confluence/display/Hive/GettingStarted#GettingStarted-Hive,Map-ReduceandLocal-Mode
Hive provided JDBC driver to query hive like JDBC, however if you are planning to run Hive queries on production system, you need Hadoop infrastructure to be available. Hive queries eventually converts into map-reduce jobs and HDFS is used as data storage for Hive tables.
I have set up a single node hadoop cluster on ubuntu.I have installed hadoop 2.6 version on in my machine.
Problem:
Everytime i create HIVE tables and load data into it , i can see the data by querying on it but once i shut-down my hadoop , tables gets wiped out. Is there any way i can retain them or is there any setting i am missing?
I tried some online solution provided , but nothing worked , kindly help me out with this.
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Thanks
B
The hive table data is on the hadoop hdfs, hive just add a meta data and provide users sql like commands to prevent them from writing basic MR jobs.So if you shutdown the hadoop cluster,Hive cant find the data in the table.
But if you are saying when you restart the hadoop cluster, the data is lost.That's another problem.
seems you are using default derby as metastore.configure the hive metastore.i am pointing the link.please fallow it.
Hive is not showing tables
I have data in a PostgreSQL DB and I'd like to get it, treat it and save it to a HBase DB. Is it possible to distribute somehow the JDBC operation in a Map operation?
Yes you can do that by DBInputFormat:
DBInputFormat uses JDBC to connect to data sources. Because JDBC is widely implemented, DBInputFormat can work with MySQL, PostgreSQL, and several other database systems. Individual database vendors provide JDBC drivers to allow third-party applications (like Hadoop) to connect to their databases.
The DBInputFormat is an InputFormat class that allows you to read data from a database. An InputFormat is Hadoop’s formalization of a data source; it can mean files formatted in a particular way, data read from a database, etc. DBInputFormat provides a simple method of scanning entire tables from a database, as well as the means to read from arbitrary SQL queries performed against the database.
LINK
I think you're looking for Sqoop, which is designed to import from SQL servers to HDFS stack technologies. It puts the data it gets from a JDBC connection into HDFS, thereby splitting it across your Hadoop NameNodes. I believe this is what you are looking for.
SQl to hadOOP = SQOOP, get it?
Sqoop can import into HBase. See this link.