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From "Dmitriy V. Ryaboy (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (PIG-2835) Optimizing the convertion from bytes to Integer/Long
Date Sun, 02 Sep 2012 22:39:07 GMT

     [ https://issues.apache.org/jira/browse/PIG-2835?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Dmitriy V. Ryaboy updated PIG-2835:
-----------------------------------

       Resolution: Fixed
    Fix Version/s: 0.11
           Status: Resolved  (was: Patch Available)

+1, applied to trunk. Thanks Jie!
                
> Optimizing the convertion from bytes to Integer/Long
> ----------------------------------------------------
>
>                 Key: PIG-2835
>                 URL: https://issues.apache.org/jira/browse/PIG-2835
>             Project: Pig
>          Issue Type: Improvement
>            Reporter: Jie Li
>             Fix For: 0.11
>
>         Attachments: PIG-2835.1.patch
>
>
> Currently Pig doesn't support lazy see/de, so as one of the best practices, we recommend
users not to declare types in the schema so that Pig will guess the right types and cast them
lazily. However, if Pig guesses a wrong type, especially mistakes a double field as an integer
field, the overhead of casting is tremendous due to the exception handling.
> See Utf8StorageConverter#bytesToIntege. It first casts bytes to Integer by Integer.parseInt(),
and if exception occurs, it tries to cast it to Double by Double.parseDouble() and convert
it back to Integer. The problem is that the exception handling can be 10x slower than the
actual casting. bytesToLong has the same problem. Below is a mini-benchmark:
> {code}        
>         int i;
>         Exception ex = null;
>         long start = System.nanoTime();
>         for (i = 0; i < 100000000; i++) {
>             try {
>                 // Double.parseDouble(i+ ".0");
>                 // Integer.parseInt(i + ".0");
>                 Integer.parseInt(i + "");
>                 // Double.parseDouble(i + "");
>             } catch (NumberFormatException e) {
>                 ex = e;
>             }
>         }
>         System.out.println("time: " + (System.nanoTime() - start)
>                 / 1000000000.0);
>         if (ex != null) {
>             ex.printStackTrace();
>         }
> {code}
> And the results:
> ||casting||running time(sec)||
> |Double.parseDouble(i+ ".0");| 17 |
> |Integer.parseInt(i + ".0");| *118* |
> |Integer.parseInt(i + "");| 13 |
> |Double.parseDouble(i + "");| 16 |
> We can see Integer.parseInt(i + ".0") is 10x slower than the other due to the exception
handling.
> This issue was found when I benchmark TPC-H Query 1, for which Pig was terribly slower
than Hive:
> {code}
> LineItems = LOAD '$input/lineitem' USING PigStorage('|') AS (orderkey, partkey, suppkey,
linenumber, quantity, extendedprice, discount, tax, returnflag, linestatus, shipdate, commitdate,
receiptdate, shipinstruct, shipmode, comment);
> SubLineItems = FILTER LineItems BY shipdate <= '1998-09-02';
> SubLine = FOREACH SubLineItems GENERATE returnflag, linestatus, quantity, extendedprice,
extendedprice*(1-discount) AS disc_price, extendedprice*(1-discount)*(1+tax) AS charge, discount;
> StatusGroup = GROUP SubLine BY (returnflag, linestatus);
> PriceSummary = FOREACH StatusGroup GENERATE group.returnflag AS returnflag, group.linestatus
AS linestatus, SUM(SubLine.quantity) AS sum_qty, SUM(SubLine.extendedprice) AS sum_base_price,
SUM(SubLine.disc_price) as sum_disc_price, SUM(SubLine.charge) as sum_charge, AVG(SubLine.quantity)
as avg_qty, AVG(SubLine.extendedprice) as avg_price, AVG(SubLine.discount) as avg_disc, COUNT(SubLine)
as count_order;
> SortedSummary = ORDER PriceSummary BY returnflag, linestatus;
> STORE SortedSummary INTO '$output/Q1out';
> {code}
> After declaring three double fields as double, the performance was boosted. 
> || pig without types || pig with three doubles || hive ||
> | 76 min | 34 min | 16 min |
> Besides recommending users to declare actual double fields as double, we can also improve
the casting to avoid this happening. Maybe the easiest way is to remove the Integer.parseInt
and only use the Double.parseDouble and convert back to Integer. The mini benchmark above
shows Double.parseDouble + range checking + Integer.valueOf(Double.intValue()) takes about
17 seconds. I think the small percent of extra overhead (3 seconds compared to Integer.parseInt())
is acceptable as it won't be the dominant bottleneck?

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