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From: Nkechi Achara <nkachara@googlemail.com>
Date: Thu, 29 Dec 2016 16:29:01 +0100
Message-ID: <CAJF+B4v+m4upnfAgp_WNdQ6MVwDah5nFHHGu0Y8DxfQxBbtgAw@mail.gmail.com>
Subject: Re: Reading specific column family and columns in Hbase table through spark
To: user@hbase.apache.org
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archived-at: Thu, 29 Dec 2016 15:29:19 -0000

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Hey Mich,

Are you setting the column family / qualifier values in the config?

e.g.

config.set(TableInputFormat.SCAN_COLUMN_FAMILY, "cf") // column family
config.set(TableInputFormat.SCAN_COLUMNS, "cf1:cq1 cf1:cq2") // column
qualifier

As you already have the results when you use newAPIHadoopRDD then you can
cast it to a conversion function too, like:

val r: Result
r.getValue(<Column Family as Bytes>, <column Qualifier as Bytes>) this will
either retrieve the value in Bytes or null if it does not exist.


Thanks,

K

On 29 December 2016 at 13:10, Mich Talebzadeh <mich.talebzadeh@gmail.com>
wrote:

> Hi,
>
> I have a routine in Spark that iterates  through Hbase rows and tries to
> read columns.
>
> My question is how can I read the correct ordering of columns?
>
> example
>
> val hBaseRDD = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
>       classOf[org.apache.hadoop.hbase.io.ImmutableBytesWritable],
>       classOf[org.apache.hadoop.hbase.client.Result])
>
> val parsed = hBaseRDD.map{ case(b, a) => val iter = a.list().iterator();
>             ( Bytes.toString(a.getRow()).toString,
>             Bytes.toString( iter.next().getValue()).toString,
>             Bytes.toString( iter.next().getValue()).toString,
>             Bytes.toString( iter.next().getValue()).toString,
>             Bytes.toString(iter.next().getValue())
> )}
>
> The above reads the column family columns sequentially. How can I force it
> to read specific columns only?
>
>
> Thanks
>
>
> Dr Mich Talebzadeh
>
>
>
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