Hi,
Now I tested the "count" method. It returns the same result as the flatmap.groupBy(0).sum(1) method.

Furthermore, the Hbase contains nearly 100 mio. rows but the result is 102 mio.. This means that the HbaseInput reads more rows than the HBase contains.

Best Regards,
Hilmi

Am 08.06.2015 um 23:29 schrieb Fabian Hueske:
Hi Hilmi,

I see two possible reasons:

1) The data source / InputFormat is not properly working, so not all HBase records are read/forwarded, or
2) The aggregation / count is buggy

Roberts suggestion will use an alternative mechanism to do the count. In fact, you can count with groupBy(0).sum() and accumulators at the same time. If both counts are the same, this will indicate that the aggregation is correct and hint that the HBase format is faulty.

In any case, it would be very good to know your findings. Please keep us updated.

One more hint, if you want to do a full aggregate, you don't have to use a "dummy" key like "a". Instead, you can work with Tuple1<Long> and directly call sum(0) without doing the groupBy().

Best, Fabian

2015-06-08 17:36 GMT+02:00 Robert Metzger <rmetz...@apache.org <mailto:rmetz...@apache.org>>:

    Hi Hilmi,

    if you just want to count the number of elements, you can also use
    accumulators, as described here [1].
    They are much more lightweight.

    So you need to make your flatMap function a RichFlatMapFunction,
    then call getExecutionContext().
    Use a long accumulator to count the elements.

    If the results with the accumulator are consistent (the exact
    element count), then there is a severe bug in Flink. But I suspect
    that the accumulator will give you the same result (off by +-5)

    Best,
    Robert


    [1]: http://slideshare.net/robertmetzger1/apache-flink-hands-on

    On Mon, Jun 8, 2015 at 3:04 PM, Hilmi Yildirim
    <hilmi.yildi...@neofonie.de <mailto:hilmi.yildi...@neofonie.de>>
    wrote:

        Hi,
        I implemented a simple Flink Batch job which reads from an
        HBase Cluster of 13 machines and with nearly 100 million rows.
        The hbase version is 1.0.0-cdh5.4.1. So, I imported
        hbase-client 1.0.0-cdh5.4.1.
        I implemented a flatmap which creates a tuple ("a", 1L) for
        each row . Then, I use groupBy(0).sum(1).writeAsTest. The
        result should be the number of rows. But, the result is not
        correct. I run the job multiple times and the result
        flactuates by +-5. I also run the job for a smaller table with
        100.000 rows and the result is correct.

        Does anyone know the reason for that?

        Best Regards,
        Hilmi

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