Hi Patrick,
In Impala 131, when you update tables and metadata, do you still need to run
'invalidate metadata' in impala-shell? My understanding is that it is a pull
architecture to refresh the metastore on the catalogd in Impala, not sure if
this still applies to this case since you are updating the Hive metastore data
when creating the external tables.
If the 'invalidate metadata' still applies, I would point this to an Impala
problem since HiveContext is passive and depends on when and who invoke the
command. The underneath driver is still Hiveserver2 to Hive (I haven't looked
into the Spark code, not sure if they are using the ql.Driver class, however,
I'm assuming it is HS2 here in Spark) where Impala needs to fetch the metadata
from Hive-metastore. HiveContext should update the Hive-metastore when you
create the table, but this doesn't mean it will trigger Impala's catalogd to
pull in the latest metadata which is cached on catalogd.
This is probably not a Parquet related answers but more of the background how
Impala works with Hive, and how Spark updates data into Hive?
AL
Date: Sat, 2 Aug 2014 10:30:27 +0200
Subject: Re: Spark SQL, Parquet and Impala
From: mcgloin.patr...@gmail.com
To: user@spark.apache.org
Hi Michael,
Thanks for your reply. Is this the correct way to load data from Spark into
Parquet? Somehow it doesn't feel right. When we followed the steps described
for storing the data into Hive tables everything was smooth, we used
HiveContext and the table is automatically recognised by Hive (and Impala).
When we loaded the data into Parquet using the method I described we used both
SQLContext and HiveContext. We had to manually define the table using the
CREATE EXTERNAL in Hive. Then we have to refresh to see changes.
So the problem isn't just the refresh, its that we're unsure of the best
practice for loading data into Parquet tables. Is the way we are doing the
Spark part correct in your opinion?
Best regards,Patrick
On 1 August 2014 19:32, Michael Armbrust <mich...@databricks.com> wrote:
So is the only issue that impala does not see changes until you refresh the
table? This sounds like a configuration that needs to be changed on the impala
side.
On Fri, Aug 1, 2014 at 7:20 AM, Patrick McGloin <mcgloin.patr...@gmail.com>
wrote:
Sorry, sent early, wasn't finished typing.
CREATE EXTERNAL TABLE ....
Then we can select the data using Impala. But this is registered as an
external table and must be refreshed if new data is inserted.
Obviously this doesn't seem good and doesn't seem like the correct solution.
How should we insert data from SparkSQL into a Parquet table which can be
directly queried by Impala?
Best regards,Patrick
On 1 August 2014 16:18, Patrick McGloin <mcgloin.patr...@gmail.com> wrote:
Hi,
We would like to use Spark SQL to store data in Parquet format and then query
that data using Impala.
We've tried to come up with a solution and it is working but it doesn't seem
good. So I was wondering if you guys could tell us what is the correct way to
do this. We are using Spark 1.0 and Impala 1.3.1.
First we are registering our tables using SparkSQL:
val sqlContext = new
SQLContext(sc)sqlContext.createParquetFile[ParqTable]("hdfs://localhost:8020/user/hive/warehouse/ParqTable.pqt",
true)
Then we are using the HiveContext to register the table and do the insert:
val hiveContext = new HiveContext(sc)import
hiveContext._hiveContext.parquetFile("hdfs://localhost:8020/user/hive/warehouse/ParqTable.pqt").registerAsTable("ParqTable")
eventsDStream.foreachRDD(event=>event.insertInto("ParqTable"))
Now we have the data stored in a Parquet file. To access it in Hive or Impala
we run
