Optimize Pig request

Question

I want to execute a pig command in embedded java program. For moment, I try Pig in local mode. My data file size is around 15MB but the execution of this command is very long so I think my script need optimizations...

My script :

A = LOAD 'data' USING PigPrismeLoader('data.xml');
filter_response_time_less_than_1_s = FILTER A BY (response_time < 1000.0);
filter_response_time_between_1_s_and_2_s = FILTER A BY (response_time >= 1000.0 AND response_time < 1999.0);
filter_response_time_between_greater_than_2_s = FILTER A BY (response_time >= 2000.0);
star__zne_asfo_access_log = FOREACH ( COGROUP A BY (date_day,url,date_minute,ret_code,serveur), filter_response_time_between_greater_than_2_s BY (date_day,url,date_minute,ret_code,serveur), filter_response_time_less_than_1_s BY (date_day,url,date_minute,ret_code,serveur), filter_response_time_between_1_s_and_2_s BY (date_day,url,date_minute,ret_code,serveur) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_asfo_url,date_minute,zne_http_code,zne_asfo_server),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymd = FOREACH ( COGROUP A BY (date_day,date_year,date_month), filter_response_time_between_greater_than_2_s BY (date_day,date_year,date_month), filter_response_time_less_than_1_s BY (date_day,date_year,date_month), filter_response_time_between_1_s_and_2_s BY (date_day,date_year,date_month) )
{
        GENERATE
                FLATTEN(group) AS (date_day,date_year,date_month),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymd_ret_url = FOREACH ( COGROUP A BY (date_day,url,date_year,date_month), filter_response_time_between_greater_than_2_s BY (date_day,url,date_year,date_month), filter_response_time_less_than_1_s BY (date_day,url,date_year,date_month), filter_response_time_between_1_s_and_2_s BY (date_day,url,date_year,date_month) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_asfo_url,date_year,date_month),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymd_ret_code = FOREACH ( COGROUP A BY (date_day,ret_code,date_year,date_month), filter_response_time_between_greater_than_2_s BY (date_day,ret_code,date_year,date_month), filter_response_time_less_than_1_s BY (date_day,ret_code,date_year,date_month), filter_response_time_between_1_s_and_2_s BY (date_day,ret_code,date_year,date_month) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_http_code,date_year,date_month),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymd_ret_url_server = FOREACH ( COGROUP A BY (date_day,url,date_year,date_month,serveur), filter_response_time_between_greater_than_2_s BY (date_day,url,date_year,date_month,serveur), filter_response_time_less_than_1_s BY (date_day,url,date_year,date_month,serveur), filter_response_time_between_1_s_and_2_s BY (date_day,url,date_year,date_month,serveur) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_asfo_url,date_year,date_month,zne_asfo_server),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymd_ret_code_server = FOREACH ( COGROUP A BY (date_day,ret_code,date_year,date_month,serveur), filter_response_time_between_greater_than_2_s BY (date_day,ret_code,date_year,date_month,serveur), filter_response_time_less_than_1_s BY (date_day,ret_code,date_year,date_month,serveur), filter_response_time_between_1_s_and_2_s BY (date_day,ret_code,date_year,date_month,serveur) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_http_code,date_year,date_month,zne_asfo_server),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymdi_server = FOREACH ( COGROUP A BY (date_day,date_minute,date_year,date_month,serveur), filter_response_time_between_greater_than_2_s BY (date_day,date_minute,date_year,date_month,serveur), filter_response_time_less_than_1_s BY (date_day,date_minute,date_year,date_month,serveur), filter_response_time_between_1_s_and_2_s BY (date_day,date_minute,date_year,date_month,serveur) )
{
        GENERATE
                FLATTEN(group) AS (date_day,date_minute,date_year,date_month,zne_asfo_server),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymdhi_url = FOREACH ( COGROUP A BY (date_day,url,date_minute,date_year,date_month), filter_response_time_between_greater_than_2_s BY (date_day,url,date_minute,date_year,date_month), filter_response_time_less_than_1_s BY (date_day,url,date_minute,date_year,date_month), filter_response_time_between_1_s_and_2_s BY (date_day,url,date_minute,date_year,date_month) )
{
        GENERATE
                FLATTEN(group) AS (date_day,zne_asfo_url,date_minute,date_year,date_month),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
agg__zne_asfo_access_log_ymdhi = FOREACH ( COGROUP A BY (date_day,date_minute,date_year,date_month), filter_response_time_between_greater_than_2_s BY (date_day,date_minute,date_year,date_month), filter_response_time_less_than_1_s BY (date_day,date_minute,date_year,date_month), filter_response_time_between_1_s_and_2_s BY (date_day,date_minute,date_year,date_month) )
{
        GENERATE
                FLATTEN(group) AS (date_day,date_minute,date_year,date_month),
                (long)SUM((bag{tuple(long)})A.response_time) AS response_time,
                COUNT(filter_response_time_less_than_1_s) AS response_time_less_than_1_s,
                COUNT(filter_response_time_between_1_s_and_2_s) AS response_time_between_1_s_and_2_s,
                COUNT(filter_response_time_between_greater_than_2_s) AS response_time_between_greater_than_2_s,
                COUNT(A) AS nb_hit;
};
STORE star__zne_asfo_access_log INTO 'star__zne_asfo_access_log' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymd INTO 'agg__zne_asfo_access_log_ymd' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymd_ret_url INTO 'agg__zne_asfo_access_log_ymd_ret_url' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymd_ret_code INTO 'agg__zne_asfo_access_log_ymd_ret_code' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymd_ret_url_server INTO 'agg__zne_asfo_access_log_ymd_ret_url_server' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymd_ret_code_server INTO 'agg__zne_asfo_access_log_ymd_ret_code_server' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymdi_server INTO 'agg__zne_asfo_access_log_ymdi_server' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymdhi_url INTO 'agg__zne_asfo_access_log_ymdhi_url' USING PigStorage('\t', '-schema');
STORE agg__zne_asfo_access_log_ymdhi INTO 'agg__zne_asfo_access_log_ymdhi' USING PigStorage('\t', '-schema');

Any ideas ?

Answer 1

Your script might need optimization, but as said in the comments, this is a tiny speck of data for Hadoop.

Hadoop does not perform well for such small data (even upto Gigabytes).

This is because Hadoop, designed to process massive amounts of data, involves a complex processing framework which takes time to setup. If you consider a large dataset, this setup time is negligible, but if your working with 15MB of data, setting up the framework would take much longer than actually processing that data.