---
abstract: |
    MapReduce is a popular programming model and an associated implementation for parallel processing big data in the distributed environment. Since large scaled MapReduce data centers usually provide services to many users, it is an essential problem to preserve the privacy between different applications in the same network. In this paper, we propose SDPMN, a framework that using *software defined network* (SDN) to distinguish the network between each application, which is a manageable and scalable method. We design this framework based on the existing SDN structure and Hadoop networks. Since the rule space of each SDN device is limited, we also propose the rule placement optimization for this framework to maximize the hardware supported isolated application networks. We state this problem in a general MapReduce network and design a heuristic algorithm to find the solution. From the simulation based evaluation, with our algorithm, the given network can support more privacy preserving application networks with SDN switches.\
author:
- '\'
title: 'SDPMN: Privacy Preserving MapReduce Network Using SDN'
---

Software Defined Network, MapReduce, Privacy

Introduction
============

MapReduce is the most popular programming model for large data processing with parallel and distributed environment [@Dean2008]. Since the large clusters usually provide services to different users all over the Internet, it is hard to preserve the privacy of user’s data with traditional network structure [@Zhou2010].

There are some existing works focus on the privacy problem in MapReduce [@McSherry2009][@Roy2010]. These works usually bring some additional overhead to influence the performance of MapReduce. Adopting *software defined network* (SDN) or the OpenFlow protocol is another way to preserve privacy between users in the MapReduce network, which can distinguish network links between each users [@Mogul2010].

Privacy leakage might take place in the Layer 2 switches, including the virtual switch in cloud environment, by the sniffer and ARP poisoning-based attack [@Nam2010]. SDN based network virtualization is an efficient method to isolated network to resist the potential data leakage in the data forwarding path. While virtualized the whole network is complex and resource-intensive, it is much appropriate that isolating the network forwarding paths in the specific network level.

SDN is an approach of computer networking, which allows the network administrator to manage network services through abstraction of hardware level functionality [@McKeown2009]. All hardware devices are managed by a centralized controller, and the network applications are deployed on this controller to implement different network functions. In the privacy preserving, the network is divided to distinguished virtual networks for each user [@Chowdhury2009].

In this paper, we propose a framework named *Software Defined Privacy Preserving MapReduce Network* (SDPMN), in which the entire network are divided to distinguished groups and each groups are isolated in the Layer 2 switches by SDN technology. In this framework, all packets are forwarded by SDN switches directly with different rules. We design this framework with existing SDN technology and Hadoop structure.

SDN enabled switches usually equip *ternary content addressable memory* (TCAM) for forwarding network packets [@McKeown2008]. Since it is power hungry, expensive and takes up quite a bit of silicon space, the storage space of TCAM in each device is limited. Ordinarily, as it is hard to place all rules in the switches, many rules are stored in the controller with the performance drawback [@Qazi2013].

In SDPMN, since forwarding paths are implemented by rules in the related SDN switches directly, the space for storing these rules is not enough with existing SDN hardware. Therefore, with the design of the SDPMN framework, we state rule placement optimization problem to maximize the application number with limited rule space. After that, we propose a heuristic algorithm to solve this problem. To evaluate the efficiency of our algorithm, we take some simulation and analyze the result to compare the existing method.

The main contributions of this paper are summarized as follows.

-   We propose a privacy preserving scenario in the leaf switches to forward application packets by the SDN forwarding rules directly instead of the traditional ARP protocols.

-   We model the privacy preserving MapReduce network scenario and state the problem to find an optimized rule placement that maximum application groups for preserve user privacy are stored in the switches with minimum performance loss.

-   We design a heuristic algorithm and find the solution for the placement problem.

The rest of this paper is summarized as follows. We discuss the motivation of the work in Section \[sec:motiv\]. In section \[sec:statement\], we introduce the framework design and the rule placement problem statement. We also introduce our heuristic algorithm to solve the placement problem in this section. In section \[sec:eva\], we evaluate the demonstration of our design to verify our methodology. In the last section, we conclude our work and discuss the future work.

Related Works
=============

In this section, we introduce some existing works focusing on the isolation and security of MapReduce network. First, we discuss the works on the network virtualization. Then, we introduce some works on the privacy preserving in MapReduce networks.

Network virtualization is a technology to isolate the network to different virtual networks for different users or applications.

Bavier et al. [@Bavier2006] propose the virtual network infrastructure, which allows network researchers to evaluate their protocols and services in a realistic environment with a high degree network control. From their work, the virtualized network performs good efficiency to support experiments and other applications. This work only focuses on the IP level without any consideration on the Level 2 switches.

ShadowNet [@Chen2009] is another network evaluation infrastructure based on the network virtualization. Similarly, it also uses the router virtualization and designs a network controller to manage the virtual networks. Meanwhile, the network virtualization can provide safe environment for users. However, they did not describe the details how to ensure testing safely.

Webb et al. [@Webb2011] introduces a network that individual application can control the topology switching for deciding best path to route data among their nodes. In their paper, it is mentioned that a $k$ isolation problem to isolate networks by limited hardware capacity. They use an allocation to find a topology that connects the task’s nodes that is minimally shared with other tasks.

Drutskoy et al. [@Drutskoy2013] design an architecture named FlowN, which can give each application or task the illusion of its own address space, topology, and controller. Actually, the FlowN architecture is a network virtualization without the SDN context. Even it mentioned that they improve the network scalability, they did not describe the security and rule placement for many applications.

The network virtualization is very important to provide isolated virtual network for different application. The problem is, they focus on how to create virtual networks, which needs substantial resource like the space of TCAM or others.

Privacy is a major topic of concern whenever large amounts of sensitive data are used in MapReduce. Even though there are many privacy preserving works to protect the data privacy, a few of works focus on the security issue of MapReduce.

Airavat [@Roy2010] is privacy preserving system that provides strong security and privacy guarantees for distributed computations. By integration of mandatory access control and differential privacy, Airavat makes data providers control their security policy to protect their privacy. Since it is an efficient work to resist the leakage of data privacy, there is no consideration about the potential leakage in the network.

Wei et al. [@Wei2009] proposed a secure scheme named SecureMR which focuses at protecting the computation integration issue of MapReduce. SecureMR detects malicious behavior of mappers by sending same tasks to multiple mappers, and compares the result consistency. This work needs the master node and reduce be secure, it seems a little hard if some malicious users exist in the MapReduce cluster.

Huang et al. [@huang2012] proposes a trusted services by verifying the MapReduce result. They focus on detecting cheating services under the MapReduce environment based on watermark injection and random sampling methods. While the privacy leakage is hard to influence the computation result, we do not consider result verification an efficient method to preserve privacy.

Motivation {#sec:motiv}
==========

In this section, we first describe the threat model to introduce the privacy preserving problem in the multiple user MapReduce networks. Then, with this threat model, we discuss the privacy preserving MapReduce network.

Threat Model
------------

![Example of the potential threat in MapReduce network[]{data-label="fig:thret_mode"}](./thret_mode.eps){width="2.5in"}

For better understanding the privacy problem in MapReduce networks, we describe an example to introduce the threat model. This example shows that a MapReduce network will leak data privacy between different users. As shown in Fig. \[fig:thret\_mode\], there are two users in a MapReduce network: one has some privacy data and the other one is a potential malicious user. Both of them submit their applications to this MapReduce data center. In the traditional network, the MapReduce nodes, including Map nodes and Reduce nodes, are connected by many Layer 2 access switches (leaf switches) [@Al-Fares2008]. These access switches are connected by some interconnection switches or more complex network.

First, the MapReduce system such as Hadoop assigns some nodes as working nodes for the normal user and the malicious user. After assignment, the normal user sends the private data to the working nodes. After that, these data are translated to the switches ($s1$, $s2$ and $s3$) in MapReduce procedures. However, it is possible that the working nodes of the malicious user also connect to some of these switches ($s1$, $s2$ and $s3$). Since the leaf switches are usually Layer 2 switches, which are connected by Ethernet or other cheap solutions, the working nodes for malicious user, who uses sniffer or other attacks like Man-in-the-middle attack, can get the packets transferred in these switches. Even though the main implementations of MapReduce like Hadoop adopt secure connections between working nodes, it is possible to get the privacy data by some existing attack methods [@Khan2012].

Privacy Preserving with SDN
---------------------------

![Example to illustrate forwarding rules for privacy preserving[]{data-label="fig:privacy_flow"}](./privacy_flow.eps){width="2.5in"}

  Port     Node
  -------- --------
  Port 1   Node 1
  Port 2   Node 2
  Port 3   Node 3
  Port 4   Node 4

  : Ports in Fig. \[fig:privacy\_flow\]

\[tab:node\_port\]

  Forwarding Rules
  -------------------------------------------------------------------------
  IF IP = 10.0.0.1 THEN MAC $\leftarrow$ 00:00:00:01, PORT $\leftarrow$ 1
  IF IP = 10.0.0.2 THEN MAC $\leftarrow$ 00:00:00:02, PORT $\leftarrow$ 2
  IF IP = 10.0.0.3 THEN MAC $\leftarrow$ 00:00:00:03, PORT $\leftarrow$ 3
  IF IP = 10.0.0.4 THEN MAC $\leftarrow$ 00:00:00:04, PORT $\leftarrow$ 4

  : Forwarding Rules in Fig. \[fig:privacy\_flow\]

\[tab:flows\]

SDN is a network structure that all switches are controlled by the controller. As a result, if we deploy SDN switches as all switches in the network, the path of each packet can be defined by the applications rather than the basic network protocols. In the MapReduce network, with SDN network, we can isolate the network by the forwarding rules [@Shin2013].

To study the SDN network for privacy preserving in MapReduce network, we use an example to illustrate isolation by forwarding rules as shown in Fig. \[fig:privacy\_flow\]. There are node 1, 2, 3 and 4, connect to an SDN switch. The connected port of each node is described in the table shown in TABLE \[tab:node\_port\]. To preserve the privacy, we use four rules to limit the potential sniffer or other attacker in the node beside the destination. With the rules illustrated in the table shown in TABLE \[tab:flows\], each packet is only forwarded to the port connected to the destination IP address. As an example, each packet sent to node 2 with the destination IP address 10.0.0.2 will be forwarded to port 2 after setting the correct MAC address.

Unlike the traditional network virtualization, since the potential threats are not relevant to the upper network level such as IP packet forwarding, we only use the SDN rules to isolate network in the Layer 2 switches. Considering the nodes connected to each leaf switch are fixed with the number of available ports, it is acceptable to place the rules for network isolation between applications.

Framework Design and Problem statement {#sec:statement}
======================================

![SDPMN framework and the MapReduce network[]{data-label="fig:system_design"}](system_design.eps){width="2.5in"}

In this section, we first introduce the design of SDPMN framework. With this framework, we state this problem to optimize the maximum groups with limited rule space in each switch.

Framework Design
----------------

From the main structure shown in Fig. \[fig:system\_design\], the framework consists of two parts: group management and the SDN application.

For each application, group management gets the information about all mapper, reducer and other related nodes in the network. After that, group management divides these nodes to groups. The nodes for one application are organized to one group. When the user submits an application to the Job Tracker, Job Tracker informs group management the application information. The name node also connects group management to inform the information about mappers and reducers.

With the information of applications and their mappers and reducers, group management maintains a table to store the correspondences between applications and servers. When the nodes of application are changed by the Job Track, the new node information will be transferred to group management to update the group table dynamically.

The SDN application generates rules to isolate the network in Layer 2 switches with the group table from group management and the network topology. In this SDN application, one module is used for the management of network topology and the other modules generate rules and manages these rules.

Since the network topology will be changed frequently in some virtual machine based networks, the topology management will update the relationship between switches, nodes and groups dynamically. When the topology is updated, rule management generates the newest rules. Since the switch space is limited to store all needed rules, the SDN application selects parts of rules for placement to switches. For the groups whose rules are not placed in the switches, it will bring additional overhead to forward the packets in these groups to guarantee the privacy. Since it is relevant to the controller implementation and the network design [@Yu2010][@Moshref2012], we do not discuss this overhead in the placement. At last, the SDN application updates the subset of rules to the corresponding switches. We introduce the rule placement problem in the final part of this section.

![Example of the SDPM[]{data-label="fig:statement"}](./statement.eps){width="2.5in"}

Problem Statement
-----------------

  Notation       Description
  -------------- ----------------------------------------------------
  $N_k$          Node set for each MapReduce application
  $n_i$          Node in set $N_k$
  $S_k$          Switch set for each MapReduce application
  $s_j$          Switch in set $S_k$
  $C$            Capacity of each switch
  $R$            Rule space cost for each rule
  $\mathbb{N}$   Number of application groups supported by switches

  : Notations in the rule placement problem

\[tab:notation\]

Now we discuss the rule placement problem in SDPMN framework. Since existing data centers are not dedicated for MapReduce usage, it is no need to control forwarding of each packet. For each MapReduce application, the nodes for Mapper and Reducer are different. Therefore, for these different node sets, the network should be reconfigured with different rules to define the forwarding path of each packet. We propose a MapReduce driving privacy preserving network shown in Fig. \[fig:statement\].

In this network, we first define $N_1$, $N_2$, ..., $N_n$ to denote the node set for each MapReduce application. For each node set, $N_k$, we use $n_i\in N_k$ to denote each node included in $N_i$. In Fig. \[fig:statement\], the node set $N_1$ of Application 1 is $\{n_1, n_2, n_3\}$ and the node set $N_2$ of Application 2 is $\{n_3, n_4\}$. With these node sets, we define $S_1$, $S_2$, ... , $S_n$ to denote the set of leaf switches for each application. For example, in Fig. \[fig:statement\], the switch set $S_1$ of Application 1 is $\{s_1, s_2\}$ and the switch set $S_2$ of Application 2 is $\{s_2\}$. For each switch set $S_i$, we also define $s_j\in S_i$ to denote each switch included in $S_i$. We use value $X_{ij}$ to denote the connections between nodes and switches as (\[eq:connection\]). $$\label{eq:connection}
X_{ij}=\left\{\begin{matrix}
0 & \ no\ connection\ between\ n_i\ and\ s_j \\
1 & \ n_i\ connected\ to\ s_j
\end{matrix}\right.$$

For privacy preserving, we consider the number of rules for each node in each application is the same and use $R$ to denote this rule count. Since the hardware space of each SDN switch is usually too expansive to support enough rules, as shown in (\[eq:capacity\]), we define the number $C$ to denote the capacity of each switch and the capacity of each switch $s_j$ cannot support rule placement of all applications. $$\label{eq:capacity}
R\sum_{k=1}^n\sum_{i\in N_k}X_{ij} > C \text{, for } s_j \in S$$

Therefore, in the rule placement, we can only place parts of rules of the switches with the best efficiency. We define set $\mathbb{N}$ to denote the node sets whose rules are placed in switches. With this set, the rule number of each switch is less than its capacity as (\[eq:placement\]).

$$\label{eq:placement}
R\sum_{k=1}^{|\mathbb{N}|}\sum_{i\in N_k}X_{ij} \leq C \text{, for } s_j \in S$$

From the model of existing works, we consider that each group has the same security priority to simplify the placement problem [@Roy2010]. Therefore, with the capacity limitation, we state the rule placement problem in the SDPMN that, with given node sets of each application, find a set $\mathbb{N}$ in which rules of each node are placed in switches and maximize the size of $\mathbb{N}$.

Algorithm Design {#sec:alg}
----------------

Sort node sets $N_1$, $N_2$, ..., $N_n$ that $|S_1| <|S_2| <...<|S_n|$. \[sort\] $\mathbb{N} \leftarrow \emptyset $ \[N\] \[begin\] $p \leftarrow 0$ $placed \leftarrow True$ \[place\] \[constrant\]

$placed \leftarrow False$ break \[placed\] Break $p\leftarrow p+1$ \[put\] $\mathbb{N} \leftarrow \mathbb{N} \cup \{N_k\}$ \[afterput\] \[end\]

To solve the placement problem, we propose a heuristic algorithm with greedy strategy shown in Algorithm \[alg:placement\]. Since each group has the same privacy priority, the main procedure of this algorithm is to place the rules from small group to large group.

First, we sort all node sets by the size of their corresponding switch sets in line \[sort\]. After sorting, we define the empty set $\mathbb{N}$ in line \[N\] as the result of the algorithm. From line \[begin\] to line \[end\], we use a *for* loop to place rules of each node set iteratively. In this loop, we select the $N_k$ who has the smallest size of the corresponding switch set in unallocated node sets. For each node $n_i$ in $N_k$, we traverse each switch in the corresponding switch set $S_k$ from line \[place\] to \[placed\]. In line \[constrant\], we check whether the switch has enough space for rule placement of $n_i$. If there is not enough space for placing rules of $n_i$, it means the rule placement for $N_k$ is failed. With this failure, the algorithm breaks the loop and places rules of the next node set. If success, the capacity of the switch $s_j$ is decreased by $R$. From line \[put\] to line \[afterput\], if the rules of nodes in $N_k$ are all placed, $N_k$ is put to the result set $\mathbb{N}$.

From this algorithm, we can easily get the worst time complexity is $\mathcal{O}(n\sum_{k=1}^{n}|N_k||S_k|)$. For most of the applications, since the number of nodes is much smaller than the scale of the nodes in the entire data center, the complexity can be simplified to $\mathcal{O}(n^2)$.

Evaluation {#sec:eva}
==========

In this section, we evaluate the performance of the greedy algorithm discussed in section \[sec:alg\] by simulation. To simulate large scale network topology, we implement some python scripts with networkx library. We defined two different network in the simulation: one network is for simulating the networks in normal MapReduce data center and the other network is for simulating the cloud environment. We also use two types of node scale to simulate the light workload and heavy workload.

First, we introduce the simulation setting of these different networks and node scale. Usually, in the cloud environment, there are more nodes connected to each leaf switch than the normal data center. For the normal network, we set 20 nodes connected to each leaf switch. For the cloud environment, we set 400 nodes connected to each leaf switch. Meanwhile, the number of nodes of the normal network is set to 1000 while the number of nodes in the cloud environment is set to 20000. Both of these networks have the same number of leaf switches which is set to 50. We define two types of node scale for light workload and heavy workload. For the light workload, the number of working nodes is set from 10 to 100 in average distribution. For the heavy workload which needs more working nodes, the number is set from 100 to 200 in the average distribution. To simplify the simulation, we set the cost of each rule to 1 and the maximum space of each switch is set to 1000. This simplification is from the existing SDN switches. Usually, to implement a forwarding rule, it needs about several entries in OpenFlow protocol and the entries supported by normal switch are a few of thousands [@Curtis2011].

With the simulation settings, we evaluate the performance of our algorithm in these networks with different node scale. We first test the performance of the algorithm with the normal data center setting. Since there is no related algorithm for this problem, we use a random placement as the comparison. The performance is shown in Fig. \[fig:eva\_normal\]. With light workload, the greedy placement shows much better than random placement with different rule space shown in Fig. \[fig:result\_com1\]. The maximum number of supported groups is near 2000 with the greedy placement when the rule space of each switch is set to 1000. However, when the workload becomes heavy and needs more working nodes, the supported groups are much less as shown in Fig. \[fig:result\_com2\]. Although the greedy placement performs better than the random placement, the maximum supported groups is less than 160, which is only 8% of the result with light workload by the same rule space.

With more nodes increased in the cloud data center network condition, the performance of rule placement is almost the same with the normal network condition shown in Fig. \[fig:eva\]. With light workload setting, the maximum supported number of application groups by the greedy placement are near the 6 times than the number by the random placement shown in Fig. \[fig:result\_com3\]. When the workload increased, the supported groups by the greedy algorithm placement are no more than 140 with 1000 rule space in each switch shown in Fig. \[fig:result\_com4\]. From the result of the simulation, with the light workload of small scale of working nodes in each group, the greedy placement has good efficiency in both normal data center and cloud environment network. For the heavy workload, it seems better to use some task placements rather than simple rule placement optimization.

Unlike the random placement, in our greedy algorithm, the size of each group is considered. Therefore, more groups with small size can be placed firstly. For the small size groups, since the probability of overlapping between groups is small, the number of supported groups is near to the ideal placement. However, with the average size of groups increased and the frequently overlapping between groups, the number of groups supported by the network is greatly decreased. This is the reason why the groups supported in the network by the greedy placement are only two times than that of random placement.

Conclusion and Future Work
==========================

In this paper, we propose a framework named SDPMN. In this framework, the network forwarding is guaranteed by SDN rules to avoid the potential threats that leak privacy data to malicious users in the same network. Since the rule space of each switch is limited, we state the problem to maximize the number of application groups whose rules are placed in the SDN switches. We propose a heuristic algorithm with the greedy strategy and evaluate this algorithm by simulation. From the simulation results, with the greedy placement algorithm, the given network can support more application groups than random placement. Since the application groups and users are varied in different periods, we will discuss the dynamic placement in the future work. Meanwhile, if the application needs more nodes from the data center network, the rule space of each switch is hard to support many application groups. Considering there are many repeating and redundant rules between application groups, we will take some optimization in the future work.

Acknowledgment {#acknowledgment .unnumbered}
==============

This work is supported by National 973 Basic Research Program of China under grant No. 2014CB340600.

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McNeill leads the way in pool for Langley Olympians

Hugh McNeill led the way, winning all five of his races to win the nine-year-old boys' aggregate trophy.

McNeill and his Langley Olympians teammates were competing at the UBC Aquatic Centre in the annual Vancouver Pacific Swim Club 10 and under invitational meet./

It was held on Dec. 1.

Bryce Dong, 10, also had a great showing, shaving 14 seconds off his 200 IM time and posting personal bests in the 50 back, 50 breast and 50 free to finish fourth overall in the 10-year-old boys' competition.

A pair of nine-year-olds, Quinn St. Pierre and Alanna Picotte, placed sixth and eighth, respectively, in their age group.

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#include "preferences/usersettings.h"
#include <lilv-0/lilv/lilv.h>

class LV2Backend : public EffectsBackend {
    Q_OBJECT
  public:
    LV2Backend(QObject* pParent);
    virtual ~LV2Backend();

    void enumeratePlugins();
    const QList<QString> getEffectIds() const;
    const QSet<QString> getDiscoveredPluginIds() const;
    EffectManifestPointer getManifest(const QString& effectId) const;
    LV2Manifest* getLV2Manifest(const QString& effectId) const;
    bool canInstantiateEffect(const QString& effectId) const;
    EffectPointer instantiateEffect(EffectsManager* pEffectsManager,
                                    const QString& effectId);

  private:
    void initializeProperties();
    LilvWorld* m_pWorld;
    QHash<QString, LilvNode*> m_properties;
    QHash<QString, LV2Manifest*> m_registeredEffects;

    QString debugString() const {
        return "LV2Backend";
    }
};

#endif // LV2BACKEND_H


Gynecologic surgery and surgical morbidity in mentally handicapped women.
A multidisciplinary clinic recognizing the reproductive health concerns of mentally handicapped women was organized in 1985. Thirty-three of the 300 women seen in the clinic required surgery. Thirty-seven operations, including 13 major abdominal and two major vaginal operations, were performed. Uterine leiomyoma and ovarian neoplasm were the most common gynecologic conditions requiring major surgery. No complications developed in women undergoing minor procedures; however, six patients undergoing major abdominal procedures developed significant postoperative complications. Because thorough and complete pelvic examinations are often difficult to accomplish in mentally handicapped women, these patients may have increased risk for the delayed diagnosis of gynecologic conditions that require major abdominal or vaginal surgery. Mentally handicapped women with significant physical handicaps are at increased risk of developing postoperative complications, and the postoperative stay may be prolonged.


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Summary

2014 BAFTA Film Award Nomination: Special Visual Effects

2014 BAFTA Film Award Nomination: Make-up and hair

From Academy Award® - winning filmmaker Peter Jackson comes The Hobbit: The Desolation of Smaug, the second in a trilogy of films adapting the enduringly popular masterpiece The Hobbit, by J.R.R. Tolkien. The three films tell a continuous story set in Middle-earth 60 years beforeThe Lord of the Rings, which Jackson and his filmmaking team brought to the big screen in the blockbuster trilogy that culminated with the Oscar® - winning The Lord of the Rings: The Return of the King.

The Hobbit: The Desolation of Smaug continues the adventure of the title character Bilbo Baggins as he journeys with the Wizard Gandalf and thirteen Dwarves, led by Thorin Oakenshield, on an epic quest to reclaim the Lonely Mountain and the lost Dwarf Kingdom of Erebor. Having survived the beginning of their unexpected journey, the Company continues East, encountering along the way the skin-changer Beorn and a swarm of giant Spiders in the treacherous forest of Mirkwood. After escaping capture by the dangerous Wood-elves, the Dwarves journey to Lake-town, and finally to the Lonely Mountain itself, where they must face the greatest danger of all - a creature more terrifying than any other; onewhich will test not only the depth of their courage but the limits of their friendship and the wisdom of the journey itself - the Dragon Smaug.


Q:

Proper way to do a try/except with catchall in javascript

What would be the correct way to do the following:
try {
    card.focus();
} catch(ReferenceError e) {
    console.log(e)
} catch (e) {
    console.log('damn')
}

In python it would be:
try:
    card.focus()
except ReferenceError as e:
    print e
except:
    print 'damn'

A:

Use the keyword instanceOf in order to check the Error type.

try {
  card.focus();
} catch (error) {
  if (error instanceof ReferenceError) console.log("Not defined!");
}


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do you really think they would trade kobe for lee, q, jeffries jones and dickau? they would try and dump radmanovic to us i think. anyway that talent level isnt really on par... lee would have to be thrown in with another superstar and not be the best or second best player in the package.

Actually, aquiring Kobe might look a little better after his performance in the FIBA Tournament....playing with players who can get the job done is exactly what kobe needs to win....an he cant do that in LA...or with any team making a run for him in the western conference. With that being said, i think kobe will either go to Chicago or new york. I feel he might go to chicago because it will definitely solve the lakers problem at the 1 spot, but that would be it. An paxon dosent want to break up his young team. I really think he would choose NYC because its NEW YORK firstly, secondly we could make a realistic trade of
Q.Rich.......8.1 mil
Crawford...7.9 mil
Nate.......1.2 mil
Lee.....990 thousand
Jones...3.3 mil (expireing contract)
1st round draft pick (isiah can spot talent late in the draft)

for

Kobe....18.1 mil
Maurice evans...1.2 mil
2 rnd draft pick

Our lineup will then be one to compete and contend for a title in the NBA...

this link clearly shows that kobe will b disappointed having to feed the ball to kwame brown in the post....kobe dosnet need another scoring title, he wants to win a chamionship, an he ain ga do it with LA fa sure

Sam Smith of the Chicago Tribune did a wrap up on the Americas tournament in Vegas and briefly discussed Kobe Bryant's future. Let me nip this in the bud before anyone gets hysterical, because Sam suggests the Knicks will be major players in trying to get Kobe.

Sam merely speculated on what we've all been speculating since Kobe first came out and said he wanted out, so don't read too much into this. There is nothing new.

Where there is hope, there can be faith
Where there is faith, miracles can occur

why not giving up Marbury and one or two young players? This could solve the Lakers problems on the point guard spot and since it doesn't take so many years until Marbury's contract expires, the Lakers might see it as a chance to to keep themselves in the media (cf. Vick, my ho et cetera) and going over to rebuilding as soon as Marbury is in Italy.

For the Knicks to get Kobe, Isiah would have to make a trade with the some key players along with expiring contracts and unprotected picks. I think this is the trade scenario that I think would make that deal happen:
To Lakers:
Eddie Curry
Renaldo Balkman and/or David Lee
Fred Jones
Dan Dickau
Wilson Chandler and/or Randolph Morris
1 to 2 Unprotected #1 Picks

To Knicks:
Kobe Bryant

I don't think the Lakers would want Crawford but I think they would love to have Curry after loosing O'Neil. So, I think that scenario would get Kobe to NY for sure. You might have to give up more young guys if you wanted to keep either Lee or Balkman. So, the 3 young guys (the 2 draft picks from this past draft and Chandler). Not sure if they would want to dump Vladimir's contract as well. If so, they might want the Knicks to add Rose's contract to the trade and force the Knicks take his 3 remaining years.

why not giving up Marbury and one or two young players? This could solve the Lakers problems on the point guard spot and since it doesn't take so many years until Marbury's contract expires, the Lakers might see it as a chance to to keep themselves in the media (cf. Vick, my ho et cetera) and going over to rebuilding as soon as Marbury is in Italy.

Who would be our point guard? Nate? Marbury is a lock because he's good and because there's no one else out there available on his level. I expect to see Randolph's name in the trade. This is going to upset allot of you guys but ether Randolph or Lee are out of here. My guess is Lee due to his contract.

hometheaterguy i think your trade is more in the ballpark. the only way we can get him for less is if he holds out of training camp and theyre forced to trade him. but as long as hes willing to stay in LA theyre not gonna take anything short of overwhelming.


Hip-hop icon and weed aficionado Wiz Khalifa announced on Tuesday that he will be releasing a line of Khalifa Kush Enterprises cannabis oils in Canada. The new products will be produced under a partnership between Khalifa, Khalifa Kush Enterprises Canada, and Supreme Cannabis.

“I’m excited to bring our first products to Canada and launch KKE Oils,” Khalifa said in a press release. “They are an awesome, high-in-THC product that everyone will love. This is a legendary moment that will be followed by many more game changing releases KKE will launch with Supreme Cannabis over the next year.”

Products Target Adult-Use Market

The new line of products are a “recreational focused oil, developed for the consumer who wants the convenience, high THC potency and precise dosing offered by a cannabis oil,” the company said.

The debut offering of KKE Cannabis Oils will be produced from flower of the Sensi Star strain cultivated by Supreme Cannabis subsidiary 7 Acres at its indoor facility in Kincardine, Ontario. John Fowler, the founder of Supreme Cannabis, said that exceptional cannabis products depend on exceptional plants.

“We firmly believe that a high-quality input supports high-quality output and KKE Oil embodies this belief,” Fowler said. “We are excited to launch one of the first recreational focused cannabis oils in Canada with Wiz Khalifa and the KKE team. KKE Oils are easy to consume, effective, and deliver the aromatic terpene profile 7ACRES’ Sensi Star is known for.”

KKE Sensi Star oils will be available for purchase later this week in British Columbia and Ontario and in Alberta in early July. The company’s products will begin distribution in other Canadian provinces later in the year. New products from other 7 Acres strains will also launch throughout 2019.

“We can’t wait to launch the full suite of KKE products, including KKE Jean Guy Oil, later this year,” said Fowler.

Partnership Announced Last Year

Khalifa announced the partnership between KKE and Supreme Cannabis in December 2018, noting that it was the first time the company was extending its reach beyond the United States, where the firm was founded earlier that year.

“Canada is a very important place to me with the idea for ‘Kush and Orange Juice’ being created in Toronto, it’s the perfect start for the international expansion of Khalifa Kush,” he said. “My team and I have spent the past year finding a partner that shares our vision, values and passion for cannabis. The team at Supreme Cannabis understands the importance of high quality cannabis and how to produce high quality cannabis at scale. I am very excited to be working with them to bring Khalifa Kush quality products to Canada and other international markets.”


This article focuses on the difficult issue of what exactly goes on when an individual tolerates something. It focuses on the problem of why an individual would ever choose to allow for some practice that he deerns unacceptable while having the power to do something about it. After distinguishing between different attitudes (tolerant as well as intolerant), this article argues that individuals can have various reasons for deciding to tolerate what they deern wrong. As such, we defend a broad conception of tolerance, which goes against the grain of recent literature in which tolerance is generally understood as a virtue


Q:

Jenkins - See SVN changes before build

I'm searching for some plugin, some way, to show the user (the ones that uses manual build) of our Jenkins the last SVN changes, to be more specific, what will be built if he pushes the play button.
Searching stackoverflow i´ve found some answers that looks like what I want, but aren't exactly what I need...
Can a Hudson job poll a SCM without pulling code down?
This one is saying to create a new job.. I could do that, but afraid that the user will get lost somehow, having two projects, one to see what will be built and one to actually build it.
Thanks

A:

I haven't done it, but it looks like the Build Pipeline plugin (https://wiki.jenkins-ci.org/display/JENKINS/Build+Pipeline+Plugin) will do what you want.  We use this plugin for its views - I noticed it also adds a "Manually Execute Downstream Project" option to build steps.
You still create two jobs, one to poll and one to build.  Have the build job identified as a manual execution downstream project from the polling job, and you're done.  I think.

A:

You need this Subversion Release Manager plugin:
https://wiki.jenkins-ci.org/display/JENKINS/Subversion+Release+Manager
Look at the screenshot in that link.
It allows you to see all SVN revisions, and then select from which revision to build


Q:

Android Studio - Error Building - Android tasks have already been created

Getting the following error when building the project:
Error:(2, 0) Android tasks have already been created.
This happens when calling android.applicationVariants,
android.libraryVariants or android.testVariants.
Once these methods are called, it is not possible to
continue configuring the model.
Root build.gradle:
buildscript {
      repositories {
        jcenter()
      }
      dependencies {
        classpath 'com.android.tools.build:gradle:1.1.0'
      }
}
apply plugin: 'android'

android {
    compileSdkVersion 'Google Inc.:Google APIs:19'
    buildToolsVersion '19.1.0'
    defaultConfig {
       versionCode 5
       versionName '5'
       targetSdkVersion 19
       minSdkVersion 10
       applicationId 'tsp.movil'
    }
}
dependencies {
     compile 'com.google.android.gms:play-services:7.0.0'
     compile 'com.android.support:support-v4:22.1.1'
}

App build.gradle:
android {
     compileSdkVersion 'Google Inc.:Google APIs:19'
     buildToolsVersion '19.1.0'
     defaultConfig {
        applicationId "tsp.movil"
        minSdkVersion 10
        targetSdkVersion 19
        versionCode 5
        versionName '5'
     }
     buildTypes {
         release {
            minifyEnabled false
            proguardFiles getDefaultProguardFile('proguard-android.txt'),      'proguard-rules.txt'
         }
     }
     productFlavors {
     }
}
dependencies {
    compile 'com.android.support:support-v4:19.1.0'
    compile 'com.google.android.gms:play-services:+'
    compile files('libs/zbar.jar')
}

A:

Your Top Level build.gradle file should only have the configuration common for all modules of your project.
make the following changes :
Root build.gradle file should have only this piece of code
buildscript {
      repositories {
        jcenter()
      }
      dependencies {
        classpath 'com.android.tools.build:gradle:1.1.0'
      }
}

allprojects{
    repositories {
        jcenter()
      }
}


include(TestingMacros)

add_regression_test(cfour-sp-rohf-ccsd_t_ "psi;cfour;addon;cc")


China’s merger watchdog gets tough on clearance dodgers

HONG KONG – A week after China’s two largest taxi-hailing firms announced plans for a $35 billion (27 billion pounds) merger, lawyers say China’s merger control watchdog is cracking down on companies that don’t seek approval for deals, and it wants greater powers to punish them.

Last Tuesday the Ministry of Commerce (MOFCOM) antimonopoly bureau took the unusual step of revealing that taxi operator Didi Chuxing had not yet sought clearance to buy rival Uber China’s assets but would need to if the deal met its thresholds – which was widely interpreted more as an order than a statement.

It is not yet clear if the deal breaches MOFCOM’s thresholds or if a clearance application has been filed. “We are in close communication with the authorities,” a Didi spokesman said. Lawyers said companies sometimes fail to file due to ambiguity over how the revenue or control thresholds apply to certain structures, or because the deal is on the borderline.

There is debate over whether Didi should include driver payments in its revenue calculation, which could push the deal over MOFCOM’s thresholds. Others, however, hope to dodge the MOFCOM review process, which has a reputation for being slow and opaque, fearing delays may kill the tie-up.

“Some players do not have the knowledge, but some companies deliberately avoid filing, including some state-owned enterprises, as it can be quite a lengthy and uncertain timetable,” said Liyong Jiang, partner at Gaopeng & Partners and a former MOFCOM legal official. But MOFCOM’s patience appears to be wearing thin.

Over the past 12 months, it has stepped up enforcement against such “gun-jumping”, naming, shaming and fining a total of 11 companies, including Microsoft (MSFT.O), Canada’s Bombardier (BBDb.TO) and Japan’s Hitachi (6501.T), in relation to eight deals that were not filed.

Transactions must be notified to MOFCOM before closing if the merging companies’ combined global turnover in the previous year exceeded 10 billion yuan ($1.5 billion) or their combined China income exceeds 2 billion yuan.

In May, MOFCOM said it fined Bombardier and China’s New United Group for deliberately failing to notify a 2015 joint venture because a delay might have prevented the new entity from participating in a railway project tender. It was the second time MOFCOM had fined Bombardier for gun-jumping.

Jianwei Zhang, president of Bombardier China, said the timing of the deals and the tender bidding process was complicated by the involvement of multiple regulators. He added that Bombardier cooperated fully with MOFCOM and was satisfied with its decision.

MOFCOM did not respond to requests for comment. “Companies making a joint tender bid have faced serious difficulties: if they sought antitrust approval, incorporation of the JV could be delayed and the opportunity might be gone by the time approval came,” said Adrian Emch, a partner at Hogan Lovells. “An alternative would be not to file, but this might breach the law. Damned if you do, damned if you don’t.”

HIGHER PENALTIES

Over the past 18 months, MOFCOM has significantly improved its review process, with 75 percent of deals now going through a simplified procedure that takes on average 29 days, according to data compiled by Norton Rose Fulbright.

Antitrust lawyers say this is encouraging more would-be gun-jumpers to file and has also freed up watchdog staff for investigative work. “The new procedure has allowed MOFCOM officials to focus on more substantive matters, including enforcement against noncompliance,” said Marc Waha, head of the Asia antitrust practice at Norton Rose Fulbright.

MOFCOM can force gun-jumpers to dispose of assets or unwind transactions but has so far been reluctant to use these measures if the transaction does not ultimately pose competition concerns.

The regulator has preferred instead to issue public financial penalties. It is not the fine itself – capped at just 500,000 yuan – that is causing companies to think twice before skipping a filing, but the reputational damage.

“Because the statutory maximum fine is very low, MOFCOM decided to start ‘naming and shaming’ noncompliant parties in late 2014,” said Waha. “MOFCOM officials remain frustrated, however, with some parties thinking the low sanctions are worth taking the risk, and have publicly advocated for an increase in these sanctions when China’s Antimonopoly Law is revised.”

China has scheduled a review of the law but it is not clear how long this might take or what any new maximum fine might be. In the meantime, lawyers expect more enforcement action, not least because rivals are increasingly prompting the regulator to scuttle deals.

Ride-hailing firm Yidao Yongche last year complained to MOFCOM about Didi’s previous takeover of rival Kuaidi Dache. “A number of the cases which have been sanctioned by MOFCOM appear to have been brought to MOFCOM’s attention by third parties,” said Mark Jephcott, head of the Asia competition practice at Herbert Smith Freehills. “This is another reason for companies to stay on their toes.” -Reuters


ENDGAME T-SHIRT - TROPHY

Product Code: T-TROPHY

Description

Endgame Clothing believes that intellectual passions, like chess, are at the very core of being human. Passion of the body is nothing without passion of the mind. It's our body that engages in the act, but it is our mind that provides us with the lasting joy of it.
Endgame strives to create the finest chess apparel on the planet. The thought, care and craftsmanship that go into each design are second to none.
All shirts are printed on 100% ringspun, preshrunk cotton for an amazingly comfortable playing experience. All shirts have a classic athletic look. If a looser fit is preferred, consider ordering a size larger.
The Trophy Shirt: Black shirt with large, front print design using discharge inks for a super soft feel and vintage look.

H.O. from ND writes, "Received my beautiful ebonized Winsor chess set today. It is awesome. A work of art I will treasure & play with. I can't wait to save up enough for my House of Staunton chess board."

Home of the World’s Finest Chess Pieces, Chess Boards and Chess Sets

Welcome to the official website of The House of Staunton. The House of Staunton has firmly established itself as the gold standard by which all chess pieces, chess boards and chess sets are judged. All of our luxury chess products, including our chess pieces, chess boards and chess sets, have been produced with the discerning chess collector in mind. We adhere to the highest quality standards and our master artisans handcraft our chess pieces, chess boards and chess sets out of such luxurious materials as Porcelain, Camel Bone, Genuine Ebony, Walnut Burl, and fossilized 40,000 year-old Wooly Mammoth Ivory. We invite you to indulge yourself and discover what countless other chess enthusiasts know – The House of Staunton offers the finest chess pieces, chess boards and chess sets – bar none!

Why settle for less when you can own a legendary chess set from The House of Staunton!


Q:

Trying to retrieve Send Classifications through the Marketing Cloud SOAP API

I've been trying to retrieve the send classifications associated with a business unit through the SOAP API using a SOAP envelope I found here:
Get Send Classifications using FuelSDK-PHP
*request:
<Envelope xmlns="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<Header>
    <fueloauth xmlns="https://exacttarget.com">[I Insert an OAuth Access Token Here]</fueloauth>
</Header>
<Body>
    <RetrieveRequestMsg xmlns="http://exacttarget.com/wsdl/partnerAPI">
        <RetrieveRequest>
            <ObjectType>SendClassification</ObjectType>
            <Properties>ObjectID</Properties>
            <Properties>Client.ID</Properties>
            <Properties>CustomerKey</Properties>
            <Properties>Name</Properties>
        </RetrieveRequest>
    </RetrieveRequestMsg>
</Body>

The request seems to go through, but I don't get any info about the send classifications back
*response:
<soap:Envelope xmlns:soap="http://schemas.xmlsoap.org/soap/envelope/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:wsa="http://schemas.xmlsoap.org/ws/2004/08/addressing" xmlns:wsse="http://docs.oasis-open.org/wss/2004/01/oasis-200401-wss-wssecurity-secext-1.0.xsd" xmlns:wsu="http://docs.oasis-open.org/wss/2004/01/oasis-200401-wss-wssecurity-utility-1.0.xsd">
<soap:Header>
    <wsa:Action>RetrieveResponse</wsa:Action>
    <wsa:MessageID>urn:uuid:91dd2863-f8bf-4da6-a0bb-bfe762b6524e</wsa:MessageID>
    <wsa:RelatesTo>urn:uuid:6eff6d00-820b-4255-844e-727e41e91fb8</wsa:RelatesTo>
    <wsa:To>http://schemas.xmlsoap.org/ws/2004/08/addressing/role/anonymous</wsa:To>
    <wsse:Security>
        <wsu:Timestamp wsu:Id="Timestamp-7cfc1c1b-2c03-46dd-9184-92772bc72647">
            <wsu:Created>2016-08-31T21:34:28Z</wsu:Created>
            <wsu:Expires>2016-08-31T21:39:28Z</wsu:Expires>
        </wsu:Timestamp>
    </wsse:Security>
</soap:Header>
<soap:Body>
    <RetrieveResponseMsg xmlns="http://exacttarget.com/wsdl/partnerAPI">
        <OverallStatus>OK</OverallStatus>
        <RequestID>9e8221cb-31ac-42e9-a0ca-327e65a44077</RequestID>
    </RetrieveResponseMsg>
</soap:Body>

Is there any way for me to retrieve available send classification IDs?

A:

What endpoint are you posting to?
This endpoint worked for me.
https://webservice.exacttarget.com/Service.asmx


Clifton James, best known for his indelible portrayal of a southern sheriff in two James Bond films but who was most proud of his work on the stage, has died. He was 96.

His daughter, Lynn James, said he died Saturday at another daughter's home in Gladstone, Oregon, due to complications from diabetes.

"He was the most outgoing person, beloved by everybody," Lynn James said. "I don't think the man had an enemy. We were incredibly blessed to have had him in our lives."

James often played a convincing southerner but loved working on the stage in New York during the prime of his career.

One of his first significant roles playing a southerner was as a cigar-chomping, prison floor-walker in the 1967 classic "Cool Hand Luke."

His long list of roles also includes swaggering, tobacco-spitting Louisiana Sheriff J.W. Pepper in the Bond films.

His portrayal of the redneck sheriff in "Live and Let Die" in 1973 more than held its own with sophisticated English actor Roger Moore's portrayal of Bond.

James was such a hit that writers carved a role for him in the next Bond film, "The Man with the Golden Gun," in 1974. James, this time playing the same sheriff on vacation in Thailand and the epitome of the ugly American abroad, gets pushed into the water by a baby elephant.

"He wasn't supposed to actually go in," said his daughter. "They gave him sugar in his pocket to feed the elephant. But he wasn't giving it to the elephant fast enough."

She said her father met with real southern sheriffs to prepare for his role as Pepper. Of his hundreds of roles, it was the Louisiana sheriff that people most often recognized and approached him about.

His daughter noted that her father sometimes said actors get remembered for one particular role out of hundreds.

"His is the sheriff's, but he said he would have never picked that one," she said.

George Clifton James was born May 29, 1920, in Spokane, Washington, the oldest of five siblings and the only boy. The family lost all its money at the start of the Great Depression and moved to Gladstone, just outside Portland, Oregon, where James' maternal grandparents lived.

In the 1930s, James got work with the Civilian Conservation Corps and then entered World War II in 1942 as a soldier with the U.S. Army in the South Pacific, receiving two Purple Hearts, a Bronze Star and a Silver Star.

Lynn James said one of the Purple Hearts came when a bullet pierced his helmet and zipped around the inside to come out and split his nose. The second Purple Heart, she said, came from shrapnel that knocked out many of his teeth.

She said her father rarely spoke about the war and never described events leading to his receiving the Silver Star.

"He lost too many friends," she said.

After the war, James took classes at the University of Oregon and acted in plays. Inspired, he moved to New York and launched his acting career.

Later in life, he spent the fall and spring of each year in New York. In the winter, he lived in a condo in Delray Beach, Florida. During the summer he lived in Oregon.

James' wife, Laurie, died in 2015. He is survived by two sisters, five children, 14 grandchildren and four great grandchildren.

Lynn James said a celebration of her father's life will be held in Gladstone in August, but there are no other plans so far. She said some of his ashes will likely be spread in the Clackamas River in Oregon, in which he swam as a boy, and in New York Harbor, where some of his wife's ashes were spread.