Hi,
1.1.4 is a oldish version of the JSON serde, have you tried with the most
recent from the master branch ?
On Mon, Jun 23, 2014 at 10:23 AM, Christian Link <christian.l...@mdmp.com>
wrote:
> Hi,
>
> thanks...but I need to sort things out with ONE SerDe/strategy...
> I've started with André's idea by using Roberto Congiu's SerDe and André's
> template to create a table with the right schema and loading the data
> aftrerwards.
>
> But it's not completely working...
>
> I did the following (sorry for spaming...):
>
> 1. create table and load data
>
> -- create database (if not exists)
> CREATE DATABASE IF NOT EXISTS mdmp_api_dump;
>
> -- connect to database;
> USE mdmp_api_dump;
>
> -- add SerDE for json processing
> ADD JAR /home/hadoop/lib/hive/json-serde-1.1.4-jar-with-dependencies.jar;
>
> -- drop old raw data
> DROP TABLE IF EXISTS mdmp_raw_data;
>
> -- create raw data table
> CREATE TABLE mdmp_raw_data (
> action string,
> batch array<
> struct<
> timestamp:string,
> traits:map<string,string>,
> requestId:string,
> sessionId:string,
> event:string,
> userId:string,
> action:string,
> context:map<string,string>,
> properties:map<string,string>
>
> >
> >,
> context struct<
> build:map<string,string>,
> device:struct<
> brand:string,
> manufacturer:string,
> model:string,
> release:string,
> sdk:int
> >,
> display:struct<
> density:double,
> height:int,
> width:int
> >,
> integrations:map<string,boolean>,
> library:string,
> libraryVersion:string,
> locale:map<string,string>,
> location:map<string,string>,
> telephony:map<string,string>,
> wifi:map<string,boolean>
> >,
> received_at string,
> requestTimestamp string,
> writeKey string
> )
> ROW FORMAT SERDE 'org.openx.data.jsonserde.JsonSerDe'
> STORED AS TEXTFILE;
>
> -- load data
> LOAD DATA INPATH 'hdfs:///input-api/1403181319.json' OVERWRITE INTO TABLE
> `mdmp_raw_data`;
>
> 2. run query against the "raw data" and create "formatted table":
>
> ADD JAR /home/hadoop/lib/hive/json-serde-1.1.4-jar-with-dependencies.jar;
>
> USE mdmp_api_dump;
>
> DROP TABLE IF EXISTS mdmp_api_data;
>
> CREATE TABLE mdmp_api_data AS
> SELECT DISTINCT
> a.action,
> a.received_at,
> a.requestTimestamp,
> a.writeKey,
> a.context.device.brand as brand,
> a.context.device.manufacturer as manufacturer,
> a.context.device.model as model,
> a.context.device.release as release,
> a.context.device.sdk as sdk,
> -- a.context.display.density as density,
> a.context.display.height as height,
> a.context.display.width as width,
> a.context.telephony['radio'] as tel_radio,
> a.context.telephony['carrier'] as tel_carrier,
> a.context.wifi['connected'] as wifi_connected,
> a.context.wifi['available'] as wifi_available,
> a.context.locale['carrier'] as loce_carrier,
> a.context.locale['language'] as loce_language,
> a.context.locale['country'] as loce_country,
> a.context.integrations['Tapstream'] as int_tapstream,
> a.context.integrations['Amplitude'] as int_amplitude,
> a.context.integrations['Localytics'] as int_localytics,
> a.context.integrations['Flurry'] as int_flurry,
> a.context.integrations['Countly'] as int_countly,
> a.context.integrations['Quantcast'] as int_quantcast,
> a.context.integrations['Crittercism'] as int_crittercism,
> a.context.integrations['Google Analytics'] as int_googleanalytics,
> a.context.integrations['Mixpanel'] as int_mixpanel,
> b.batch.action AS b_action,
> b.batch.context,
> b.batch.event,
> b.batch.properties,
> b.batch.requestId,
> b.batch.sessionId,
> b.batch.timestamp,
> b.batch.traits,
> b.batch.userId
> FROM mdmp_raw_data a
> LATERAL VIEW explode(a.batch) b AS batch;
>
> So far so good... (besides a silly double/int bug in the outdated SerDe)
> I thought.
>
> But it turned out, that some fields are NULL - within all records.
>
> Affected fields are:
> b.batch.event,
> b.batch.requestId,
> b.batch.sessionId,
> b.batch.userId
>
> I can see values in the json file, but neither in the "raw table" nor in
> the final table...that's really strange.
>
> An example record:
> {"requestTimestamp":"2014-06-19T14:25:26+02:00","context":{"libraryVersion":"0.6.13","telephony":{"radio":"gsm","carrier":"o2
> -
> de"},"wifi":{"connected":true,"available":true},"location":{},"locale":{"carrier":"o2
> -
> de","language":"Deutsch","country":"Deutschland"},"library":"analytics-android","device":{"brand":"htc","model":"HTC
> One
> S","sdk":16,"release":"4.1.1","manufacturer":"HTC"},"display":{"density":1.5,"width":540,"height":960},"build":{"name":"1.0","code":1},"integrations":{"Tapstream":false,"Amplitude":false,"Localytics":false,"Flurry":false,"Countly":false,"Bugsnag":false,"Quantcast":false,"Crittercism":false,"Google
> Analytics":false,"Mixpanel":false}},"batch":[{"timestamp":"2014-06-19T14:25:17+02:00","requestId":"32377337-3f99-4ac5-bfc6-d3654584655b","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Ruff
> ruff!"}},{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"fbfd45c9-cf0f-4cb3-955c-85c65220a5bd","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,08"}},{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"3a643b12-64e5-4a7c-b44b-e3e09dbc5b66","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Wow..."}},{"action":"identify","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"timestamp":"2014-06-19T14:25:19+02:00","traits":{"email":"
> do...@mdmp.com","name":"Carmelo
> Doge"},"requestId":"ef2910f4-cd4f-4175-89d0-7d91b35c229f","sessionId":"75cd18db8a364c2","userId":"doge74167705ruffruff"},{"timestamp":"2014-06-19T14:25:19+02:00","requestId":"1676bb06-abee-4135-a206-d57c4a1bc24d","sessionId":"75cd18db8a364c2","event":"TEST
> Doge App
> Usage","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{}},{"timestamp":"2014-06-19T14:25:20+02:00","requestId":"66532c8a-c5da-4852-b8b6-04df8f3052d5","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Many
> data."}},{"timestamp":"2014-06-19T14:25:21+02:00","requestId":"a1a79d8c-fe58-4567-8dec-a8d1d2ae2713","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,87"}},{"timestamp":"2014-06-19T14:25:21+02:00","requestId":"259209ac-b135-4d5f-bdac-535eccc0400e","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Wow..."}},{"timestamp":"2014-06-19T14:25:23+02:00","requestId":"59b6d57c-c7a5-4b2a-af6d-fa10ae0de60c","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Such
> App!"}},{"timestamp":"2014-06-19T14:25:24+02:00","requestId":"8b05226f-bdf5-4af8-bb91-84da1b874c6e","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Purchase","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"revenue":"0,50"}},{"timestamp":"2014-06-19T14:25:24+02:00","requestId":"0f366675-5641-4238-b2a9-176735de6edd","sessionId":"75cd18db8a364c2","event":"TEST
> Doge
> Comments","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Ruff
> ruff!"}},{"timestamp":"2014-06-19T14:25:26+02:00","requestId":"9e832534-5114-4ec1-bc20-1dcf1c354d0c","sessionId":"75cd18db8a364c2","event":"Session
> end","userId":"doge74167705ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"start":"14:25:09","end":"14:25:26"}}],"writeKey":"a8RCFSAVjmT5qyxLKMzt12kcXWOIusvw","action":"import","received_at":"2014-06-19T12:25:29.790+00:00"}
>
>
> Funny thing is, that I'm sure that I've seen these values earlier
> today...I've reloaded the data/tables several times to see if this is still
> working...well. :)
>
> I'm gonna stop for today...another try tomorrow.
>
> Thanks so far and many greetings from Berlin,
> Chris
>
>
>
>
>
>
>
>
>
>
> On Mon, Jun 23, 2014 at 6:57 PM, Sachin Goyal <sgo...@walmartlabs.com>
> wrote:
>
>>
>> You can also use hive-json-schema to automate Hive schema generation from
>> JSON:
>> https://github.com/quux00/hive-json-schema
>>
>>
>> From: Nitin Pawar <nitinpawar...@gmail.com<mailto:nitinpawar...@gmail.com
>> >>
>> Reply-To: "user@hive.apache.org<mailto:user@hive.apache.org>" <
>> user@hive.apache.org<mailto:user@hive.apache.org>>
>> Date: Monday, June 23, 2014 at 2:25 AM
>> To: "user@hive.apache.org<mailto:user@hive.apache.org>" <
>> user@hive.apache.org<mailto:user@hive.apache.org>>
>> Subject: Re: how to load json with nested array into hive?
>>
>> I think you can just take a look at jsonserde
>>
>> It does take care of nested json documents. (though you will need to know
>> entire json structure upfront)
>>
>> Here is example of using it
>> http://blog.cloudera.com/blog/2012/12/how-to-use-a-serde-in-apache-hive/
>>
>>
>>
>>
>> On Mon, Jun 23, 2014 at 2:28 PM, Christian Link <christian.l...@mdmp.com
>> <mailto:christian.l...@mdmp.com>> wrote:
>> Hi Jerome,
>>
>> thanks...I've already found "Brickhouse" and the Hive UDFs, but it didn't
>> help.
>>
>> Today I'll try again to process the json file after going through all my
>> mails...maybe I'll find a solution.
>>
>> Best,
>> Chris
>>
>>
>> On Fri, Jun 20, 2014 at 7:16 PM, Jerome Banks <jba...@tagged.com<mailto:
>> jba...@tagged.com>> wrote:
>> Christian,
>> Sorry to spam this newsgroup, and this is not a commercial
>> endorsement, but check out the Hive UDFs in the Brickhouse project (
>> http://github.com/klout/brickhouse ) (
>> http://brickhouseconfessions.wordpress.com/2014/02/07/hive-and-json-made-simple/
>> )
>>
>> You can convert arbitrary complex Hive structures to an from json with
>> it's to_json and from_json UDF's. See the blog posting for an explanation.
>>
>> -- jerome
>>
>>
>> On Fri, Jun 20, 2014 at 8:26 AM, Christian Link <christian.l...@mdmp.com
>> <mailto:christian.l...@mdmp.com>> wrote:
>> hi,
>>
>> I'm very, very new to Hadoop, Hive, etc. and I have to import data into
>> hive tables.
>>
>> Environment: Amazon EMR, S3, etc.
>>
>> The input file is on S3 and I copied it into my HDFS.
>>
>> 1. flat table with one column and loaded data into it:
>>
>> CREATE TABLE mdmp_raw_data (json_record STRING);
>> LOAD DATA INPATH 'hdfs:///input-api/1403181319.json' OVERWRITE INTO
>> TABLE `mdmp_raw_data`;
>> That worked, I can access some data, like this:
>>
>> SELECT d.carrier, d.language, d.country
>> FROM mdmp_raw_data a LATERAL VIEW json_tuple(a.data,
>> 'requestTimestamp', 'context') b AS requestTimestamp, context
>> LATERAL VIEW json_tuple(b.context, 'locale') c AS locale
>> LATERAL VIEW json_tuple(c.locale, 'carrier', 'language', 'country') d
>> AS carrier, language, country
>> LIMIT 1;
>>
>> Result: o2 - de Deutsch Deutschland
>>
>> I can also select the array at once:
>>
>> SELECT b.requestTimestamp, b.batch
>> FROM mdmp_raw_data a
>> LATERAL VIEW json_tuple(a.data, 'requestTimestamp', 'batch') b AS
>> requestTimestamp, batch
>> LIMIT 1;
>> This will give me:
>>
>>
>> [{"timestamp":"2014-06-19T14:25:18+02:00","requestId":"2ca08247-5542-4cb4-be7e-4a8574fb77a8","sessionId":"f29ec175ca6b7d10","event":"TEST
>> Doge
>> Comments","userId":"doge96514016ruffruff","action":"track","context":{"library":"analytics-android","libraryVersion":"0.6.13"},"properties":{"comment":"Much
>> joy."}}, ...]
>>
>> This "batch" may contain n events will a structure like above.
>>
>> I want to put all events in a table where each "element" will be stored
>> in a unique column: timestamp, requestId, sessionId, event, userId, action,
>> context, properties
>>
>> 2. explode the "batch" I read a lot about SerDe, etc. - but I don't get
>> it.
>>
>> - I tried to create a table with an array and load the data into it -
>> several errors
>> use explode in query but it doesn't accept "batch" as array
>> - integrated several SerDes but get things like "unknown function jspilt"
>> - I'm lost in too many documents, howtos, etc. and could need some
>> advices...
>>
>> Thank you in advance!
>>
>> Best, Chris
>>
>>
>>
>>
>>
>> --
>> Nitin Pawar
>>
>
>
--
----------------------------------------------------------
Good judgement comes with experience.
Experience comes with bad judgement.
----------------------------------------------------------
Roberto Congiu - Data Engineer - OpenX
tel: +1 626 466 1141
