[SPARK-1527] change rootDir*.getName to rootDir*.getAbsolutePath

JIRA issue: [SPARK-1527](https://issues.apache.org/jira/browse/SPARK-1527)

getName() only gets the last component of the file path. When deleting test-generated directories,
we should pass the generated directory's absolute path to DiskBlockManager.

Author: Ye Xianjin <advancedxy@gmail.com>

This patch had conflicts when merged, resolved by
Committer: Patrick Wendell <pwendell@gmail.com>

Closes #436 from advancedxy/SPARK-1527 and squashes the following commits:

4678bab [Ye Xianjin] change rootDir*.getname to rootDir*.getAbsolutePath so the temporary directories are deleted when the test is finished.
[SQL] Make it possible to create Java/Python SQLContexts from an existing Scala SQLContext.

Author: Michael Armbrust <michael@databricks.com>

Closes #761 from marmbrus/existingContext and squashes the following commits:

4651051 [Michael Armbrust] Make it possible to create Java/Python SQLContexts from an existing Scala SQLContext.
[SPARK-1784] Add a new partitioner to allow specifying # of keys per partition

This change adds a new partitioner which allows users
to specify # of keys per partition.

Author: Syed Hashmi <shashmi@cloudera.com>

Closes #721 from syedhashmi/master and squashes the following commits:

4ca94cc [Syed Hashmi] [SPARK-1784] Add a new partitioner
Implement ApproximateCountDistinct for SparkSql

Add the implementation for ApproximateCountDistinct to SparkSql. We use the HyperLogLog algorithm implemented in stream-lib, and do the count in two phases: 1) counting the number of distinct elements in each partitions, and 2) merge the HyperLogLog results from different partitions.

A simple serializer and test cases are added as well.

Author: larvaboy <larvaboy@gmail.com>

Closes #737 from larvaboy/master and squashes the following commits:

bd8ef3f [larvaboy] Add support of user-provided standard deviation to ApproxCountDistinct.
9ba8360 [larvaboy] Fix alignment and null handling issues.
95b4067 [larvaboy] Add a test case for count distinct and approximate count distinct.
f57917d [larvaboy] Add the parser for the approximate count.
a2d5d10 [larvaboy] Add ApproximateCountDistinct aggregates and functions.
7ad273a [larvaboy] Add SparkSql serializer for HyperLogLog.
1d9aacf [larvaboy] Fix a minor typo in the toString method of the Count case class.
653542b [larvaboy] Fix a couple of minor typos.
Revert "[SPARK-1784] Add a new partitioner to allow specifying # of keys per partition"

This reverts commit 92cebada09a7e5a00ab48bcb350a9462949c33eb.
[SQL] Improve column pruning.

Fixed a bug that was preventing us from ever pruning beneath Joins.

## TPC-DS Q3
### Before:
```
Aggregate false, [d_year#12,i_brand#65,i_brand_id#64], [d_year#12,i_brand_id#64 AS brand_id#0,i_brand#65 AS brand#1,SUM(PartialSum#79) AS sum_agg#2]
 Exchange (HashPartitioning [d_year#12:0,i_brand#65:1,i_brand_id#64:2], 150)
  Aggregate true, [d_year#12,i_brand#65,i_brand_id#64], [d_year#12,i_brand#65,i_brand_id#64,SUM(CAST(ss_ext_sales_price#49, DoubleType)) AS PartialSum#79]
   Project [d_year#12:6,i_brand#65:59,i_brand_id#64:58,ss_ext_sales_price#49:43]
    HashJoin [ss_item_sk#36], [i_item_sk#57], BuildRight
     Exchange (HashPartitioning [ss_item_sk#36:30], 150)
      HashJoin [d_date_sk#6], [ss_sold_date_sk#34], BuildRight
       Exchange (HashPartitioning [d_date_sk#6:0], 150)
        Filter (d_moy#14:8 = 12)
         HiveTableScan [d_date_sk#6,d_date_id#7,d_date#8,d_month_seq#9,d_week_seq#10,d_quarter_seq#11,d_year#12,d_dow#13,d_moy#14,d_dom#15,d_qoy#16,d_fy_year#17,d_fy_quarter_seq#18,d_fy_week_seq#19,d_day_name#20,d_quarter_name#21,d_holiday#22,d_weekend#23,d_following_holiday#24,d_first_dom#25,d_last_dom#26,d_same_day_ly#27,d_same_day_lq#28,d_current_day#29,d_current_week#30,d_current_month#31,d_current_quarter#32,d_current_year#33], (MetastoreRelation default, date_dim, Some(dt)), None
       Exchange (HashPartitioning [ss_sold_date_sk#34:0], 150)
        HiveTableScan [ss_sold_date_sk#34,ss_sold_time_sk#35,ss_item_sk#36,ss_customer_sk#37,ss_cdemo_sk#38,ss_hdemo_sk#39,ss_addr_sk#40,ss_store_sk#41,ss_promo_sk#42,ss_ticket_number#43,ss_quantity#44,ss_wholesale_cost#45,ss_list_price#46,ss_sales_price#47,ss_ext_discount_amt#48,ss_ext_sales_price#49,ss_ext_wholesale_cost#50,ss_ext_list_price#51,ss_ext_tax#52,ss_coupon_amt#53,ss_net_paid#54,ss_net_paid_inc_tax#55,ss_net_profit#56], (MetastoreRelation default, store_sales, None), None
     Exchange (HashPartitioning [i_item_sk#57:0], 150)
      Filter (i_manufact_id#70:13 = 436)
       HiveTableScan [i_item_sk#57,i_item_id#58,i_rec_start_date#59,i_rec_end_date#60,i_item_desc#61,i_current_price#62,i_wholesale_cost#63,i_brand_id#64,i_brand#65,i_class_id#66,i_class#67,i_category_id#68,i_category#69,i_manufact_id#70,i_manufact#71,i_size#72,i_formulation#73,i_color#74,i_units#75,i_container#76,i_manager_id#77,i_product_name#78], (MetastoreRelation default, item, None), None
```
### After
```
Aggregate false, [d_year#172,i_brand#225,i_brand_id#224], [d_year#172,i_brand_id#224 AS brand_id#160,i_brand#225 AS brand#161,SUM(PartialSum#239) AS sum_agg#162]
 Exchange (HashPartitioning [d_year#172:0,i_brand#225:1,i_brand_id#224:2], 150)
  Aggregate true, [d_year#172,i_brand#225,i_brand_id#224], [d_year#172,i_brand#225,i_brand_id#224,SUM(CAST(ss_ext_sales_price#209, DoubleType)) AS PartialSum#239]
   Project [d_year#172:1,i_brand#225:5,i_brand_id#224:3,ss_ext_sales_price#209:0]
    HashJoin [ss_item_sk#196], [i_item_sk#217], BuildRight
     Exchange (HashPartitioning [ss_item_sk#196:2], 150)
      Project [ss_ext_sales_price#209:2,d_year#172:1,ss_item_sk#196:3]
       HashJoin [d_date_sk#166], [ss_sold_date_sk#194], BuildRight
        Exchange (HashPartitioning [d_date_sk#166:0], 150)
         Project [d_date_sk#166:0,d_year#172:1]
          Filter (d_moy#174:2 = 12)
           HiveTableScan [d_date_sk#166,d_year#172,d_moy#174], (MetastoreRelation default, date_dim, Some(dt)), None
        Exchange (HashPartitioning [ss_sold_date_sk#194:2], 150)
         HiveTableScan [ss_ext_sales_price#209,ss_item_sk#196,ss_sold_date_sk#194], (MetastoreRelation default, store_sales, None), None
     Exchange (HashPartitioning [i_item_sk#217:1], 150)
      Project [i_brand_id#224:0,i_item_sk#217:1,i_brand#225:2]
       Filter (i_manufact_id#230:3 = 436)
        HiveTableScan [i_brand_id#224,i_item_sk#217,i_brand#225,i_manufact_id#230], (MetastoreRelation default, item, None), None
```

Author: Michael Armbrust <michael@databricks.com>

Closes #729 from marmbrus/fixPruning and squashes the following commits:

5feeff0 [Michael Armbrust] Improve column pruning.
SPARK-1801. expose InterruptibleIterator and TaskKilledException in deve...

...loper api

Author: Koert Kuipers <koert@tresata.com>

Closes #764 from koertkuipers/feat-rdd-developerapi and squashes the following commits:

8516dd2 [Koert Kuipers] SPARK-1801. expose InterruptibleIterator and TaskKilledException in developer api
Fix dep exclusion: avro-ipc, not avro, depends on netty.

Author: Marcelo Vanzin <vanzin@cloudera.com>

Closes #763 from vanzin/netty-dep-hell and squashes the following commits:

dfb6ce2 [Marcelo Vanzin] Fix dep exclusion: avro-ipc, not avro, depends on netty.
[SPARK-1769] Executor loss causes NPE race condition

This PR replaces the Schedulable data structures in Pool.scala with thread-safe ones from java. Note that Scala's `with SynchronizedBuffer` trait is soon to be deprecated in 2.11 because it is ["inherently unreliable"](http://www.scala-lang.org/api/2.11.0/index.html#scala.collection.mutable.SynchronizedBuffer). We should slowly drift away from `SynchronizedBuffer` in other places too.

Note that this PR introduces an API-breaking change; `sc.getAllPools` now returns an Array rather than an ArrayBuffer. This is because we want this method to return an immutable copy rather than one may potentially confuse the user if they try to modify the copy, which takes no effect on the original data structure.

Author: Andrew Or <andrewor14@gmail.com>

Closes #762 from andrewor14/pool-npe and squashes the following commits:

383e739 [Andrew Or] JavaConverters -> JavaConversions
3f32981 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pool-npe
769be19 [Andrew Or] Assorted minor changes
2189247 [Andrew Or] Merge branch 'master' of github.com:apache/spark into pool-npe
05ad9e9 [Andrew Or] Fix test - contains is not the same as containsKey
0921ea0 [Andrew Or] var -> val
07d720c [Andrew Or] Synchronize Schedulable data structures
Fixed streaming examples docs to use run-example instead of spark-submit

Pretty self-explanatory

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #722 from tdas/example-fix and squashes the following commits:

7839979 [Tathagata Das] Minor changes.
0673441 [Tathagata Das] Fixed java docs of java streaming example
e687123 [Tathagata Das] Fixed scala style errors.
9b8d112 [Tathagata Das] Fixed streaming examples docs to use run-example instead of spark-submit.
SPARK-1827. LICENSE and NOTICE files need a refresh to contain transitive dependency info

LICENSE and NOTICE policy is explained here:

http://www.apache.org/dev/licensing-howto.html
http://www.apache.org/legal/3party.html

This leads to the following changes.

First, this change enables two extensions to maven-shade-plugin in assembly/ that will try to include and merge all NOTICE and LICENSE files. This can't hurt.

This generates a consolidated NOTICE file that I manually added to NOTICE.

Next, a list of all dependencies and their licenses was generated:
`mvn ... license:aggregate-add-third-party`
to create: `target/generated-sources/license/THIRD-PARTY.txt`

Each dependency is listed with one or more licenses. Determine the most-compatible license for each if there is more than one.

For "unknown" license dependencies, I manually evaluateD their license. Many are actually Apache projects or components of projects covered already. The only non-trivial one was Colt, which has its own (compatible) license.

I ignored Apache-licensed and public domain dependencies as these require no further action (beyond NOTICE above).

BSD and MIT licenses (permissive Category A licenses) are evidently supposed to be mentioned in LICENSE, so I added a section without output from the THIRD-PARTY.txt file appropriately.

Everything else, Category B licenses, are evidently mentioned in NOTICE (?) Same there.

LICENSE contained some license statements for source code that is redistributed. I left this as I think that is the right place to put it.

Author: Sean Owen <sowen@cloudera.com>

Closes #770 from srowen/SPARK-1827 and squashes the following commits:

a764504 [Sean Owen] Add LICENSE and NOTICE info for all transitive dependencies as of 1.0
SPARK-1818 Freshen Mesos documentation

Place more emphasis on using precompiled binary versions of Spark and Mesos
instead of encouraging the reader to compile from source.

Author: Andrew Ash <andrew@andrewash.com>

Closes #756 from ash211/spark-1818 and squashes the following commits:

7ef3b33 [Andrew Ash] Brief explanation of the interactions between Spark and Mesos
e7dea8e [Andrew Ash] Add troubleshooting and debugging section
956362d [Andrew Ash] Don't need to pass spark.executor.uri into the spark shell
de3353b [Andrew Ash] Wrap to 100char
7ebf6ef [Andrew Ash] Polish on the section on Mesos Master URLs
3dcc2c1 [Andrew Ash] Use --tgz parameter of make-distribution
41b68ed [Andrew Ash] Period at end of sentence; formatting on :5050
8bf2c53 [Andrew Ash] Update site.MESOS_VERSIOn to match /pom.xml
74f2040 [Andrew Ash] SPARK-1818 Freshen Mesos documentation
SPARK-1828: Created forked version of hive-exec that doesn't bundle other dependencies

See https://issues.apache.org/jira/browse/SPARK-1828 for more information.

This is being submitted to Jenkin's for testing. The dependency won't fully
propagate in Maven central for a few more hours.

Author: Patrick Wendell <pwendell@gmail.com>

Closes #767 from pwendell/hive-shaded and squashes the following commits:

ea10ac5 [Patrick Wendell] SPARK-1828: Created forked version of hive-exec that doesn't bundle other dependencies
[SPARK-1620] Handle uncaught exceptions in function run by Akka scheduler

If the intended behavior was that uncaught exceptions thrown in functions being run by the Akka scheduler would end up being handled by the default uncaught exception handler set in Executor, and if that behavior is, in fact, correct, then this is a way to accomplish that.  I'm not certain, though, that we shouldn't be doing something different to handle uncaught exceptions from some of these scheduled functions.

In any event, this PR covers all of the cases I comment on in [SPARK-1620](https://issues.apache.org/jira/browse/SPARK-1620).

Author: Mark Hamstra <markhamstra@gmail.com>

Closes #622 from markhamstra/SPARK-1620 and squashes the following commits:

071d193 [Mark Hamstra] refactored post-SPARK-1772
1a6a35e [Mark Hamstra] another style fix
d30eb94 [Mark Hamstra] scalastyle
3573ecd [Mark Hamstra] Use wrapped try/catch in Utils.tryOrExit
8fc0439 [Mark Hamstra] Make functions run by the Akka scheduler use Executor's UncaughtExceptionHandler