I have to build a tool which will process our data storage from HBase(HFiles) to HDFS in parquet format.
Please suggest one of the best way to move data from HBase tables to Parquet tables.
We have to move 400 million records from HBase to Parquet. How to achieve this and what is the fastest way to move data?
Thanks in advance.
Regards,
Pardeep Sharma.
Please have a look in to this project tmalaska/HBase-ToHDFS
which reads a HBase table and writes the out as Text, Seq, Avro, or Parquet
Example usage for parquet :
Exports the data to Parquet
hadoop jar HBaseToHDFS.jar ExportHBaseTableToParquet exportTest c export.parquet false avro.schema
I recently opensourced a patch to HBase which tackles the problem you are describing.
Have a look here: https://github.com/ibm-research-ireland/hbaquet
Related
I am writing data into parquet files programatically with AvroParquetWriter but i also want to write parquet file with bucketing, is it possible to do same with bucketing ?
Thanks in advance!!
I am clear about the Serde available in Hive to support Avro schema for data formats. Comfortable in using avro with hive.
AvroSerDe
for say, I have found this issue against presto.
https://github.com/prestodb/presto/issues/5009
I need to choose components for fast execution cycle. Presto and impala provide much smaller execution cycle.
So, Anyone please let me clarify that which would be better in different data formats.
Primarily, I am looking for avro support with Presto now.
However, lets consider following data formats stored on HDFS:
Avro format
Parquet format
Orc format
Which is the best to use with high performance on different data formats.
?? please suggest.
Impala can read Avro data but can not write it. Please refer to this documentaion page describing the file formats supported by Impala.
Hive supports both reading and writing Avro files.
Presto's Hive Connector supports Avro as well. Thanks to David Phillips for pointing out this documentaion page.
There are different benchmarks on the internet about performance, but I would not like to link to a specific one as results heavily depend on the exact use case benchmarked.
Hi everybody
I'm quite new with bigdata, I have installed a HDFS + Hbase test database and I use Talend Big Data (an ETL) to make my test.
I would like to know : if I put a file directly in the HDFS, without going via hbase, I could never request these data ? I mean, I have to read the entire file if I want to filter data I want to chose, is that right ?
Thanks a lot for any help !
HDFS is just a distributed file system, you cannot query your files without passing by an intermidiate component.
Hbase is a nosql database that persist your data on the HDFS, use it when you need a random access to your data.
If you want to store your files on the HDFS as they are and query them, you can create an external table upon them using Hive.
The best option is to use hive on the top of the files which are on the HDFS. You can use bucketing and partitioning in the hive for performance improvement.
My Hbase table has rows that contain both serialized avro (put there using havrobase) and string data. I know that Hive table can be mapped to avro data stored in hdfs to do data analysis but I was wondering if anyone has tried to map hive to hbase table(s) that contains avro data. Basically I need to be able to query both avro and non avro data stored in Hbase, do some analysis and store the result in a different hbase table. I need the capability to do this as a batch job as well. I don't want to write a JAVA MapReduce job to do this because we have constantly changing configurations and we need to use a scripted approach. Any suggestions? Thanks in advance!
You can write an HBase co-processor to expose the avro record as regular HBase qualifiers. You can see an implementation of that in Intel's panthera-dot
As per my understanding both HIVE and HBASE are using HDFS to store the data. When we integrate HIVE and HBASE ----
How the data is moved between them? Or is it like the data wont move and it simply reflects? I am interested to know in 2 scenarios.
One: Table_1 has data and its in HIVE, Table_2 has data and its in HBASE. Now integration happened (whether this scenario possible?).
How the data movement happens? Is it from HBASE to HIVE or HIVE to HBASE.
Two: Setup as scenario One. Now for newly inserted records. Where would they go?
I am new to HBASE and interested in understanding the data movement in detail with and example.
Please improve the question if needed. Thanks in advance.
HDFS is a distributed file system that is well suited for the storage of large files but does not provide fast individual record lookups.
Hive is simply a SQL-like abstraction for interacting with the data in HDFS.
HBase is also built on top of HDFS. It provides fast reads and writes for large tables. HBase accomplishes this by storing your data in indexed "StoreFiles" that exist on HDFS for high-speed lookups.
So in both cases, data reside in HDFS. That's "where they go."
As for the details of how they work, that's a huge topic where you have to familiarize yourself with such topics as the Hive metastore and storage handlers and the HBase API. I believe this tutorial (Part 1 and Part 2) can help you.